Upgrading statsmodels 0.10 to 0.11
Unknown0.10.2 → 0.11.1
Fetching 4 releases from GitHub…0 / 4
UnknownUpgrade verdict
DepDelta is still reading the notes for this range, so breaking changes can't be ruled out yet.
In plain terms
- DepDelta is still reading the release notes in this range, so it can't rule out breaking changes yet.
- This page updates as the notes come in.
Must act Still reading release notes
DepDelta is still reading the release notes in this range. This updates as they come in.
Requires Python >=3.5 from 0.11.1 (none stated before).
API changes
Generated by DepDelta from published Python source. Not mixed with prose notes.
- removed:
export PY3 - changed:
function test(*args, **kwargs) → function test(extra_args=…, exit=…)
- removed:
function open_help(chmpath=…) - removed:
variable chmpath - added:
variable load
- added:
method ModelData.attach_mv_confint(result) - added:
method PandasData.attach_mv_confint(result) - added:
property ModelData.cov_names
- removed:
field LikelihoodModelResults.use_t - changed:
method LikelihoodModelResults.conf_int(alpha=…, cols=…, method=…) → method LikelihoodModelResults.conf_int(alpha=…, cols=…) - changed:
method Results.initialize(model, params, **kwd) → method Results.initialize(model, params, **kwargs) - added:
property LikelihoodModelResults.use_t
- removed:
export BytesIO - removed:
export HTTPError - removed:
export PY3 - removed:
export StringIO - removed:
export URLError - removed:
export asstr2 - removed:
export builtins - removed:
export bytes - removed:
export cPickle - removed:
export cStringIO - removed:
export filter - removed:
export get_class - removed:
export getargspec - removed:
export long - removed:
export map - removed:
export next - removed:
export pickle - removed:
export range - removed:
export reduce - removed:
export str - removed:
export string_types - removed:
export unichr - removed:
export unicode - removed:
export urlencode - removed:
export urljoin - removed:
export urlopen - removed:
export zip - removed:
export zip_longest
- removed:
variable NP_LT_113
- added:
export Appender - added:
export Substitution - added:
export assert_equal - added:
export make_dataframe - added:
function assert_equal(left, right) - added:
function make_dataframe() - added:
variable cache_readonly
- added:
variable PLATFORM_32 - added:
variable PLATFORM_LINUX - added:
variable PLATFORM_LINUX32
- removed:
function asstr2(s) - removed:
function asunicode(s, encoding=…) - removed:
function get_class(func) - removed:
function getargspec(func) - removed:
function next(it) - removed:
variable ArgSpec - removed:
variable BytesIO - removed:
variable HTTPError - removed:
variable PY3 - removed:
variable URLError - removed:
variable asbytes - removed:
variable asstr - removed:
variable asstr2 - removed:
variable bytes - removed:
variable cStringIO - removed:
variable filter - removed:
variable lfilter - removed:
variable lmap - removed:
variable long - removed:
variable lrange - removed:
variable lzip - removed:
variable map - removed:
variable next - removed:
variable pickle - removed:
variable range - removed:
variable reduce - removed:
variable str - removed:
variable string_types - removed:
variable unichr - removed:
variable unicode - removed:
variable urlencode - removed:
variable urljoin - removed:
variable urlopen - removed:
variable urlretrieve - removed:
variable zip - removed:
variable zip_longest
- removed:
variable NumpyVersion - removed:
variable SP_GTE_019 - removed:
variable loggamma - added:
variable SCIPY_11 - added:
variable SCIPY_GT_14
- added:
export COPYRIGHT - added:
export DESCRLONG - added:
export DESCRSHORT - added:
export NOTE - added:
export SOURCE - added:
export TITLE - added:
export load - added:
export load_pandas
- added:
function load(as_pandas=…) - added:
function load_pandas() - added:
variable COPYRIGHT - added:
variable DESCRLONG - added:
variable DESCRSHORT - added:
variable NOTE - added:
variable SOURCE - added:
variable TITLE - added:
variable variable_names
- added:
class CountModel(DiscreteModel) - added:
constructor CountModel(endog, exog, offset=…, exposure=…, missing=…, **kwargs) - added:
constructor MNLogit(endog, exog, **kwargs) - added:
method CountModel.fit(start_params=…, method=…, maxiter=…, full_output=…, disp=…, callback=…, **kwargs) - added:
method CountModel.fit_regularized(start_params=…, method=…, maxiter=…, full_output=…, disp=…, callback=…, alpha=…, trim_mode=…, auto_trim_tol=…, size_trim_tol=…, qc_tol=…, **kwargs) - added:
method CountModel.predict(params, exog=…, exposure=…, offset=…, linear=…)
- changed:
method GEE.fit(maxiter=…, ctol=…, start_params=…, params_niter=…, first_dep_update=…, cov_type=…, ddof_scale=…, scaling_factor=…) → method GEE.fit(maxiter=…, ctol=…, start_params=…, params_niter=…, first_dep_update=…, cov_type=…, ddof_scale=…, scaling_factor=…, scale=…) - changed:
method GEE.fit_regularized(pen_wt, scad_param=…, maxiter=…, ddof_scale=…, update_assoc=…, ctol=…, ztol=…, eps=…) → method GEE.fit_regularized(pen_wt, scad_param=…, maxiter=…, ddof_scale=…, update_assoc=…, ctol=…, ztol=…, eps=…, scale=…)
- changed:
method GLM.fit_regularized(method=…, alpha=…, start_params=…, refit=…, **kwargs) → method GLM.fit_regularized(method=…, alpha=…, start_params=…, refit=…, opt_method=…, **kwargs)
- changed:
function plot_fit(results, exog_idx, y_true=…, ax=…, **kwargs) → function plot_fit(results, exog_idx, y_true=…, ax=…, vlines=…, **kwargs)
- changed:
function plot_acf(x, ax=…, lags=…, alpha=…, use_vlines=…, unbiased=…, fft=…, title=…, zero=…, vlines_kwargs=…, **kwargs) → function plot_acf(x, ax=…, lags=…, *, alpha=…, use_vlines=…, unbiased=…, fft=…, missing=…, title=…, zero=…, vlines_kwargs=…, **kwargs)
- changed:
constructor KernelCensoredReg(endog, exog, var_type, reg_type, bw=…, censor_val=…, defaults=…) → constructor KernelCensoredReg(endog, exog, var_type, reg_type, bw=…, ckertype=…, ukertype=…, okertype=…, censor_val=…, defaults=…) - changed:
constructor KernelReg(endog, exog, var_type, reg_type=…, bw=…, defaults=…) → constructor KernelReg(endog, exog, var_type, reg_type=…, bw=…, ckertype=…, okertype=…, ukertype=…, defaults=…)
- added:
function tricube(h, Xi, x)
- changed:
method SlicedInverseReg.fit(**kwargs) → method SlicedInverseReg.fit(slice_n=…, **kwargs) - added:
class CovarianceReduction(_DimReductionRegression) - added:
constructor CovarianceReduction(endog, exog, dim) - added:
method CovarianceReduction.fit(start_params=…, maxiter=…, gtol=…) - added:
method CovarianceReduction.loglike(params) - added:
method CovarianceReduction.score(params) - added:
method SlicedInverseReg.fit_regularized(ndim=…, pen_mat=…, slice_n=…, maxiter=…, gtol=…, **kwargs) - added:
variable CORE
- changed:
constructor GLSAR(endog, exog=…, rho=…, missing=…, **kwargs) → constructor GLSAR(endog, exog=…, rho=…, missing=…, hasconst=…, **kwargs) - changed:
method GLS.whiten(X) → method GLS.whiten(x) - changed:
method GLSAR.iterative_fit(maxiter=…, rtol=…, **kwds) → method GLSAR.iterative_fit(maxiter=…, rtol=…, **kwargs) - changed:
method GLSAR.whiten(X) → method GLSAR.whiten(x) - changed:
method OLS.whiten(Y) → method OLS.whiten(x) - changed:
method WLS.whiten(X) → method WLS.whiten(x) - added:
class RegressionResultsWrapper(wrap.ResultsWrapper)
- added:
class VCSpec(object) - added:
constructor VCSpec(names, colnames, mats)
- added:
class RollingOLS(RollingWLS) - added:
class RollingRegressionResults(object) - added:
class RollingWLS(object) - added:
constructor RollingOLS(endog, exog, window=…, min_nobs=…, missing=…) - added:
constructor RollingRegressionResults(model, store: RollingStore, k_constant, use_t, cov_type) - added:
constructor RollingWLS(endog, exog, window=…, weights=…, min_nobs=…, missing=…) - added:
field RollingRegressionResults.remove_data - added:
function strip4(line) - added:
method RollingRegressionResults.aic() - added:
method RollingRegressionResults.bic() - added:
method RollingRegressionResults.bse() - added:
method RollingRegressionResults.centered_tss() - added:
method RollingRegressionResults.conf_int(alpha=…, cols=…) - added:
method RollingRegressionResults.cov_params() - added:
method RollingRegressionResults.df_model() - added:
method RollingRegressionResults.df_resid() - added:
method RollingRegressionResults.ess() - added:
method RollingRegressionResults.f_pvalue() - added:
method RollingRegressionResults.fvalue() - added:
method RollingRegressionResults.k_constant() - added:
method RollingRegressionResults.llf() - added:
method RollingRegressionResults.mse_model() - added:
method RollingRegressionResults.mse_resid() - added:
method RollingRegressionResults.mse_total() - added:
method RollingRegressionResults.nobs() - added:
method RollingRegressionResults.params() - added:
method RollingRegressionResults.plot_recursive_coefficient(variables=…, alpha=…, legend_loc=…, fig=…, figsize=…) - added:
method RollingRegressionResults.pvalues() - added:
method RollingRegressionResults.rsquared() - added:
method RollingRegressionResults.rsquared_adj() - added:
method RollingRegressionResults.save(fname, remove_data=…) - added:
method RollingRegressionResults.ssr() - added:
method RollingRegressionResults.tvalues() - added:
method RollingRegressionResults.uncentered_tss() - added:
method RollingRegressionResults.use_t() - added:
method RollingWLS.fit(method=…, cov_type=…, cov_kwds=…, reset=…, use_t=…, params_only=…) - added:
property RollingRegressionResults.cov_type - added:
static method RollingRegressionResults.load(fname) - added:
static method RollingWLS.from_formula(formula, data, window, weights=…, subset=…, *args, **kwargs) - added:
variable RollingStore - added:
variable common_params - added:
variable extra_base - added:
variable extra_parameters - added:
variable weight_parameters - added:
variable window_parameters
- changed:
method RLM.fit(maxiter=…, tol=…, scale_est=…, init=…, cov=…, update_scale=…, conv=…) → method RLM.fit(maxiter=…, tol=…, scale_est=…, init=…, cov=…, update_scale=…, conv=…, start_params=…)
- removed:
class Contrast(object) - removed:
class ContrastResults(object) - removed:
constructor Contrast(term, formula, name=…) - removed:
constructor ContrastResults(t=…, F=…, sd=…, effect=…, df_denom=…, df_num=…) - removed:
field Contrast.matrix - removed:
function contrastfromcols(L, D, pseudo=…) - removed:
method Contrast.compute_matrix(*args, **kw)
- removed:
class Factor(Term) - removed:
class Formula(object) - removed:
class Quantitative(Term) - removed:
class Term(object) - removed:
constructor Factor(termname, keys, ordinal=…) - removed:
constructor Formula(termlist, namespace=…) - removed:
constructor Quantitative(name, func=…, termname=…, transform=…) - removed:
constructor Term(name, func=…, termname=…) - removed:
field Formula.namespace - removed:
field Term.namespace - removed:
function interactions(terms, order=…) - removed:
function isnested(A, B, namespace=…) - removed:
method Factor.get_columns(*args, **kw) - removed:
method Factor.main_effect(reference=…) - removed:
method Factor.values(*args, **kw) - removed:
method Factor.verify(values) - removed:
method Formula.design(*args, **kw) - removed:
method Formula.hasterm(query_term) - removed:
method Formula.names() - removed:
method Formula.termcolumns(query_term, dict=…) - removed:
method Formula.termnames() - removed:
method Term.names() - removed:
variable I - removed:
variable default_namespace
- removed:
function atleast_2dcols(x)
- removed:
class CompareCox(object) - removed:
class CompareJ(object) - removed:
class HetGoldfeldQuandt(object) - removed:
class ResultsStore(object) - removed:
function acorr_breusch_godfrey(results, nlags=…, store=…) - removed:
function acorr_ljungbox(x, lags=…, boxpierce=…) - removed:
function acorr_lm(x, maxlag=…, autolag=…, store=…, regresults=…) - removed:
function breaks_AP(endog, exog, skip) - removed:
function breaks_cusumolsresid(olsresidual, ddof=…) - removed:
function breaks_hansen(olsresults) - removed:
function het_arch(resid, maxlag=…, autolag=…, store=…, regresults=…, ddof=…) - removed:
function het_breuschpagan(resid, exog_het) - removed:
function het_white(resid, exog, retres=…) - removed:
function linear_harvey_collier(res) - removed:
function linear_lm(resid, exog, func=…) - removed:
function linear_rainbow(res, frac=…) - removed:
function recursive_olsresiduals(olsresults, skip=…, lamda=…, alpha=…) - removed:
function spec_white(resid, exog) - removed:
function unitroot_adf(x, maxlag=…, trendorder=…, autolag=…, store=…) - removed:
method CompareCox.run(results_x, results_z, attach=…) - removed:
method CompareJ.run(results_x, results_z, attach=…) - removed:
method HetGoldfeldQuandt.run(y, x, idx=…, split=…, drop=…, alternative=…, attach=…) - removed:
variable adfstat - removed:
variable compare_cox - removed:
variable compare_j - removed:
variable crit_5lags0p05 - removed:
variable crvd - removed:
variable crvdg - removed:
variable examples - removed:
variable f - removed:
variable fo - removed:
variable fp - removed:
variable het_goldfeldquandt - removed:
variable mcres - removed:
variable mcressort - removed:
variable nobs - removed:
variable nrepl - removed:
variable resgq - removed:
variable resols1 - removed:
variable resstore - removed:
variable x - removed:
variable y - added:
export CompareCox - added:
export CompareJ - added:
export HetGoldfeldQuandt - added:
export OLS - added:
export ResultsStore - added:
export acorr_breusch_godfrey - added:
export acorr_ljungbox - added:
export acorr_lm - added:
export adfuller - added:
export breaks_cusumolsresid - added:
export breaks_hansen - added:
export compare_cox - added:
export compare_j - added:
export het_arch - added:
export het_breuschpagan - added:
export het_goldfeldquandt - added:
export het_white - added:
export linear_harvey_collier - added:
export linear_lm - added:
export linear_rainbow - added:
export recursive_olsresiduals - added:
export spec_white - added:
export unitroot_adf
- removed:
function test_tukey_pvalues() - removed:
variable locs - removed:
variable reject - removed:
variable reject2 - removed:
variable rvs - removed:
variable tpval - removed:
variable tpval_sorted - removed:
variable tpval_sortind - removed:
variable tt - removed:
variable x1
- removed:
function adf20(x)
- removed:
class AR(LikelihoodModel) - removed:
class Arma(LikelihoodModel) - removed:
class Garch(TSMLEModel) - removed:
class Garch0(TSMLEModel) - removed:
class GarchX(TSMLEModel) - removed:
class LikelihoodModel(Model) - removed:
class TSMLEModel(LikelihoodModel) - removed:
constructor AR(endog, exog=…, nlags=…) - removed:
constructor Arma(endog, exog=…) - removed:
constructor Garch(endog, exog=…) - removed:
constructor Garch0(endog, exog=…) - removed:
constructor GarchX(endog, exog=…) - removed:
constructor LikelihoodModel(endog, exog=…) - removed:
constructor TSMLEModel(endog, exog=…) - removed:
function garchplot(err, h, title=…) - removed:
function generate_garch(nobs, ar, ma, mu=…, scale=…) - removed:
function generate_gjrgarch(nobs, ar, ma, mu=…, scale=…, varinnovation=…) - removed:
function generate_kindofgarch(nobs, ar, ma, mu=…) - removed:
function gjrconvertparams(self, params, nar, nma) - removed:
function loglike_GARCH11(params, y) - removed:
function normloglike(x, mu=…, sigma2=…, returnlls=…, axis=…) - removed:
function sumofsq(x, axis=…) - removed:
function test_gjrgarch() - removed:
function test_misofilter() - removed:
method AR.fit(start_params=…, method=…, maxiter=…, tol=…, penalty=…) - removed:
method AR.hessian(params) - removed:
method AR.information(params) - removed:
method AR.initialize() - removed:
method AR.loglike(params) - removed:
method AR.score(params) - removed:
method Arma.fit(start_params=…, maxiter=…, method=…, tol=…) - removed:
method Arma.geterrors(params) - removed:
method Arma.hessian(params) - removed:
method Arma.initialize() - removed:
method Arma.loglike(params) - removed:
method Arma.score(params) - removed:
method Garch.geterrors(params) - removed:
method Garch.initialize() - removed:
method Garch.loglike(params) - removed:
method Garch0.geth(params) - removed:
method Garch0.initialize() - removed:
method Garch0.loglike(params) - removed:
method GarchX.convert_mod2params(ma, mu) - removed:
method GarchX.geth(params) - removed:
method GarchX.initialize() - removed:
method GarchX.loglike(params) - removed:
method LikelihoodModel.fit(start_params=…, method=…, maxiter=…, tol=…) - removed:
method LikelihoodModel.hessian(params) - removed:
method LikelihoodModel.information(params) - removed:
method LikelihoodModel.initialize() - removed:
method LikelihoodModel.loglike(params) - removed:
method LikelihoodModel.score(params) - removed:
method TSMLEModel.fit(start_params=…, maxiter=…, method=…, tol=…) - removed:
method TSMLEModel.geterrors(params) - removed:
method TSMLEModel.hessian(params) - removed:
method TSMLEModel.loglike(params) - removed:
method TSMLEModel.score(params) - removed:
variable ar - removed:
variable ar1 - removed:
variable arest - removed:
variable arma1 - removed:
variable arma1res - removed:
variable arma2 - removed:
variable arma3 - removed:
variable arma3b - removed:
variable arma3bres - removed:
variable arma3res - removed:
variable armodel - removed:
variable axis - removed:
variable err - removed:
variable errgjr - removed:
variable errgjr2 - removed:
variable errgjr3 - removed:
variable errgjr4 - removed:
variable errgjr5 - removed:
variable errls - removed:
variable erro - removed:
variable etax - removed:
variable etax3 - removed:
variable etax4 - removed:
variable etax5 - removed:
variable etaxo - removed:
variable examples - removed:
variable f - removed:
variable ggmod - removed:
variable ggmod0 - removed:
variable ggres - removed:
variable ggres0 - removed:
variable h - removed:
variable hgjr - removed:
variable hgjr2 - removed:
variable hgjr3 - removed:
variable hgjr4 - removed:
variable hgjr5 - removed:
variable ho - removed:
variable ht - removed:
variable inp - removed:
variable llf - removed:
variable llike - removed:
variable lls - removed:
variable llt - removed:
variable ma - removed:
variable nobs - removed:
variable params - removed:
variable res2 - removed:
variable res3 - removed:
variable resls - removed:
variable seed - removed:
variable sigma2 - removed:
variable start_params - removed:
variable tseries - removed:
variable varinno - removed:
variable warmup - removed:
variable x - removed:
variable x3 - removed:
variable y - removed:
variable y1
- removed:
function ECDF(values) - removed:
function fullrank(X, r=…) - removed:
function rank(X, cond=…)
- added:
export CompareCox - added:
export CompareJ - added:
export CompareMeans - added:
export DescrStatsW - added:
export Describe - added:
export FTestAnovaPower - added:
export FTestPower - added:
export FactoredPSDMatrix - added:
export GofChisquarePower - added:
export HetGoldfeldQuandt - added:
export Mediation - added:
export NormalIndPower - added:
export NullDistribution - added:
export OaxacaBlinder - added:
export RegressionFDR - added:
export Runs - added:
export SquareTable - added:
export StratifiedTable - added:
export TTestIndPower - added:
export TTestPower - added:
export Table - added:
export Table2x2 - added:
export acorr_breusch_godfrey - added:
export acorr_ljungbox - added:
export acorr_lm - added:
export anova_lm - added:
export binom_test - added:
export binom_test_reject_interval - added:
export binom_tost - added:
export binom_tost_reject_interval - added:
export breaks_cusumolsresid - added:
export breaks_hansen - added:
export chisquare_effectsize - added:
export cochrans_q - added:
export compare_cox - added:
export compare_encompassing - added:
export compare_j - added:
export corr_clipped - added:
export corr_nearest - added:
export corr_nearest_factor - added:
export corr_thresholded - added:
export cov_cluster - added:
export cov_cluster_2groups - added:
export cov_hac - added:
export cov_hc0 - added:
export cov_hc1 - added:
export cov_hc2 - added:
export cov_hc3 - added:
export cov_nearest - added:
export cov_nearest_factor_homog - added:
export cov_nw_panel - added:
export cov_white_simple - added:
export diagnostic - added:
export durbin_watson - added:
export fdrcorrection - added:
export fdrcorrection_twostage - added:
export gof - added:
export gof_chisquare_discrete - added:
export het_arch - added:
export het_breuschpagan - added:
export het_goldfeldquandt - added:
export het_white - added:
export jarque_bera - added:
export lilliefors - added:
export linear_harvey_collier - added:
export linear_lm - added:
export linear_rainbow - added:
export linear_reset - added:
export local_fdr - added:
export mcnemar - added:
export moment_helpers - added:
export multicomp - added:
export multinomial_proportions_confint - added:
export multipletests - added:
export normal_ad - added:
export omni_normtest - added:
export power_binom_tost - added:
export power_ztost_prop - added:
export powerdiscrepancy - added:
export proportion_confint - added:
export proportion_effectsize - added:
export proportions_chisquare - added:
export proportions_chisquare_allpairs - added:
export proportions_chisquare_pairscontrol - added:
export proportions_ztest - added:
export proportions_ztost - added:
export recursive_olsresiduals - added:
export runstest_1samp - added:
export runstest_2samp - added:
export sandwich_covariance - added:
export se_cov - added:
export spec_white - added:
export stattools - added:
export tt_ind_solve_power - added:
export tt_solve_power - added:
export ttest_ind - added:
export ttost_ind - added:
export ttost_paired - added:
export tukeyhsd - added:
export zconfint - added:
export zt_ind_solve_power - added:
export ztest - added:
export ztost
- added:
export anderson_statistic - added:
export kstest_exponential - added:
export kstest_fit - added:
export kstest_normal - added:
export lilliefors - added:
export normal_ad - added:
function acorr_breusch_godfrey(res, nlags=…, store=…) - added:
function acorr_ljungbox(x, lags=…, boxpierce=…, model_df=…, period=…, return_df=…) - added:
function acorr_lm(resid, nlags=…, autolag=…, store=…, *, period=…, ddof=…, cov_type=…, cov_kwargs=…) - added:
function compare_cox(results_x, results_z, store=…) - added:
function compare_j(results_x, results_z, store=…) - added:
function het_arch(resid, nlags=…, autolag=…, store=…, ddof=…) - added:
function het_breuschpagan(resid, exog_het) - added:
function het_goldfeldquandt(y, x, idx=…, split=…, drop=…, alternative=…, store=…) - added:
function het_white(resid, exog) - added:
function linear_harvey_collier(res, order_by=…) - added:
function linear_lm(resid, exog, func=…) - added:
function linear_rainbow(res, frac=…, order_by=…, use_distance=…, center=…) - added:
function spec_white(resid, exog)
- added:
function distance_correlation(x, y) - added:
function distance_covariance(x, y) - added:
function distance_covariance_test(x, y, B=…, method=…) - added:
function distance_statistics(x, y, x_dist=…, y_dist=…) - added:
function distance_variance(x) - added:
variable DistDependStat
- added:
class OaxacaBlinder(object) - added:
class OaxacaResults - added:
constructor OaxacaBlinder(endog, exog, bifurcate, hasconst=…, swap=…, cov_type=…, cov_kwds=…) - added:
constructor OaxacaResults(results, model_type) - added:
method OaxacaBlinder.three_fold() - added:
method OaxacaBlinder.two_fold() - added:
method OaxacaResults.summary()
- removed:
method TableDist.crit2(prob, n) - removed:
variable alpha - removed:
variable crit_lf - removed:
variable lf - removed:
variable size - changed:
constructor TableDist(alpha, size, crit_table) → constructor TableDist(alpha, size, crit_table, asymptotic=…, min_nobs=…, max_nobs=…)
- added:
variable recarray_warning
- removed:
function chain_dot(*arrs) - changed:
function fullrank(X, r=…) → function fullrank(x, r=…) - changed:
function isestimable(C, D) → function isestimable(c, d) - added:
function asstr2(s)
- added:
export PandasWrapper - added:
export array_like - added:
export bool_like - added:
export dict_like - added:
export float_like - added:
export int_like - added:
export string_like
- added:
function array_like(pos, name, dtype=…, ndim=…, maxdim=…, shape=…, order=…, contiguous=…)
- added:
class PandasWrapper(object) - added:
constructor PandasWrapper(pandas_obj) - added:
function array_like(obj, name, dtype=…, ndim=…, maxdim=…, shape=…, order=…, contiguous=…, optional=…) - added:
function bool_like(value, name, optional=…, strict=…) - added:
function dict_like(value, name, optional=…, strict=…) - added:
function float_like(value, name, optional=…, strict=…) - added:
function int_like(value, name, optional=…, strict=…) - added:
function string_like(value, name, optional=…, options=…, lower=…) - added:
method PandasWrapper.wrap(obj, columns=…, append=…, trim_start=…, trim_end=…)
- changed:
function webdoc(arg=…, stable=…) → function webdoc(func=…, stable=…)
- removed:
export DynamicVAR - added:
export AutoReg - added:
export STL - added:
export arima - added:
export bk_filter - added:
export cf_filter - added:
export hp_filter
- changed:
class AR(tsbase.TimeSeriesModel) → class AR(tsa_model.TimeSeriesModel) - added:
class AutoReg(tsa_model.TimeSeriesModel) - added:
constructor AutoReg(endog, lags, trend=…, seasonal=…, exog=…, hold_back=…, period=…, missing=…) - added:
method AutoReg.fit(cov_type=…, cov_kwds=…, use_t=…) - added:
method AutoReg.hessian(params) - added:
method AutoReg.information(params) - added:
method AutoReg.initialize() - added:
method AutoReg.loglike(params) - added:
method AutoReg.predict(params, start=…, end=…, dynamic=…, exog=…, exog_oos=…) - added:
method AutoReg.score(params) - added:
property AutoReg.ar_lags - added:
property AutoReg.df_model - added:
property AutoReg.exog_names - added:
property AutoReg.hold_back - added:
property AutoReg.seasonal
- added:
export ARIMA
- added:
export dowj - added:
export lake - added:
export oshorts - added:
export sbl
- added:
variable dowj
- added:
variable lake
- added:
variable oshorts
- added:
variable sbl
- added:
function burg(endog, ar_order=…, demean=…)
- added:
function durbin_levinson(endog, ar_order=…, demean=…, unbiased=…)
- added:
function gls(endog, exog=…, order=…, seasonal_order=…, include_constant=…, n_iter=…, max_iter=…, tolerance=…, arma_estimator=…, arma_estimator_kwargs=…)
- added:
function hannan_rissanen(endog, ar_order=…, ma_order=…, demean=…, initial_ar_order=…, unbiased=…)
- added:
function innovations(endog, ma_order=…, demean=…) - added:
function innovations_mle(endog, order=…, seasonal_order=…, demean=…, enforce_invertibility=…, start_params=…, minimize_kwargs=…)
- added:
function statespace(endog, exog=…, order=…, seasonal_order=…, include_constant=…, enforce_stationarity=…, enforce_invertibility=…, concentrate_scale=…, start_params=…, fit_kwargs=…)
- added:
function yule_walker(endog, ar_order=…, demean=…, unbiased=…)
- added:
class ARIMA(sarimax.SARIMAX) - added:
class ARIMAResults(sarimax.SARIMAXResults) - added:
class ARIMAResultsWrapper(sarimax.SARIMAXResultsWrapper) - added:
constructor ARIMA(endog, exog=…, order=…, seasonal_order=…, trend=…, enforce_stationarity=…, enforce_invertibility=…, concentrate_scale=…, trend_offset=…, dates=…, freq=…, missing=…) - added:
method ARIMA.fit(start_params=…, transformed=…, includes_fixed=…, method=…, method_kwargs=…, gls=…, gls_kwargs=…, cov_type=…, cov_kwds=…, return_params=…, low_memory=…)
- added:
class SARIMAXParams(object) - added:
constructor SARIMAXParams(spec) - added:
method SARIMAXParams.to_dict() - added:
method SARIMAXParams.to_pandas() - added:
property SARIMAXParams.ar_params - added:
property SARIMAXParams.ar_poly - added:
property SARIMAXParams.exog_params - added:
property SARIMAXParams.is_complete - added:
property SARIMAXParams.is_invertible - added:
property SARIMAXParams.is_stationary - added:
property SARIMAXParams.is_valid - added:
property SARIMAXParams.ma_params - added:
property SARIMAXParams.ma_poly - added:
property SARIMAXParams.params - added:
property SARIMAXParams.reduced_ar_poly - added:
property SARIMAXParams.reduced_ma_poly - added:
property SARIMAXParams.seasonal_ar_params - added:
property SARIMAXParams.seasonal_ar_poly - added:
property SARIMAXParams.seasonal_ma_params - added:
property SARIMAXParams.seasonal_ma_poly - added:
property SARIMAXParams.sigma2
- added:
class SARIMAXSpecification(object) - added:
constructor SARIMAXSpecification(endog=…, exog=…, order=…, seasonal_order=…, ar_order=…, diff=…, ma_order=…, seasonal_ar_order=…, seasonal_diff=…, seasonal_ma_order=…, seasonal_periods=…, trend=…, enforce_stationarity=…, enforce_invertibility=…, concentrate_scale=…, trend_offset=…, dates=…, freq=…, missing=…) - added:
method SARIMAXSpecification.constrain_params(unconstrained) - added:
method SARIMAXSpecification.construct_trend_data(nobs, offset=…) - added:
method SARIMAXSpecification.construct_trend_names() - added:
method SARIMAXSpecification.join_params(exog_params=…, ar_params=…, ma_params=…, seasonal_ar_params=…, seasonal_ma_params=…, sigma2=…) - added:
method SARIMAXSpecification.split_params(params, allow_infnan=…) - added:
method SARIMAXSpecification.unconstrain_params(constrained) - added:
method SARIMAXSpecification.validate_estimator(estimator) - added:
method SARIMAXSpecification.validate_params(params) - added:
property SARIMAXSpecification.ar_names - added:
property SARIMAXSpecification.exog_names - added:
property SARIMAXSpecification.is_ar_consecutive - added:
property SARIMAXSpecification.is_integrated - added:
property SARIMAXSpecification.is_ma_consecutive - added:
property SARIMAXSpecification.is_seasonal - added:
property SARIMAXSpecification.k_ar_params - added:
property SARIMAXSpecification.k_exog_params - added:
property SARIMAXSpecification.k_ma_params - added:
property SARIMAXSpecification.k_params - added:
property SARIMAXSpecification.k_seasonal_ar_params - added:
property SARIMAXSpecification.k_seasonal_ma_params - added:
property SARIMAXSpecification.ma_names - added:
property SARIMAXSpecification.param_names - added:
property SARIMAXSpecification.seasonal_ar_names - added:
property SARIMAXSpecification.seasonal_ma_names - added:
property SARIMAXSpecification.valid_estimators
- added:
function standardize_lag_order(order, title=…) - added:
function validate_basic(params, length, allow_infnan=…, title=…)
- removed:
method ARMAResults.cov_params() - removed:
method ARMAResults.pvalues() - removed:
variable ar - removed:
variable arma - removed:
variable arma13css - removed:
variable arma14css - removed:
variable arma22 - removed:
variable arma22_css - removed:
variable arma31css - removed:
variable arma41css - removed:
variable data - removed:
variable dta - removed:
variable mod - removed:
variable res - removed:
variable res13css - removed:
variable res14css - removed:
variable res22 - removed:
variable res22css - removed:
variable res31css - removed:
variable res41css - removed:
variable resar - removed:
variable wpi - removed:
variable y - removed:
variable y_arma13 - removed:
variable y_arma14 - removed:
variable y_arma22 - removed:
variable y_arma31 - removed:
variable y_arma41 - changed:
class ARMA(tsbase.TimeSeriesModel) → class ARMA(tsa_model.TimeSeriesModel) - changed:
class ARMAResults(tsbase.TimeSeriesModelResults) → class ARMAResults(tsa_model.TimeSeriesModelResults) - changed:
method ARMA.predict(params, start=…, end=…, exog=…, dynamic=…) → method ARMA.predict(params, start=…, end=…, exog=…, dynamic=…, **kwargs) - changed:
method ARMAResults.predict(start=…, end=…, exog=…, dynamic=…) → method ARMAResults.predict(start=…, end=…, exog=…, dynamic=…, **kwargs) - added:
method ARMAResults.cov_params_default() - added:
variable REPEATED_FIT_ERROR
- changed:
function arma2ar(ar, ma, lags=…, **kwargs) → function arma2ar(ar, ma, lags=…) - changed:
function arma2ma(ar, ma, lags=…, **kwargs) → function arma2ma(ar, ma, lags=…) - changed:
function arma_acf(ar, ma, lags=…, **kwargs) → function arma_acf(ar, ma, lags=…) - changed:
function arma_generate_sample(ar, ma, nsample, sigma=…, distrvs=…, burnin=…) → function arma_generate_sample(ar, ma, nsample, scale=…, distrvs=…, axis=…, burnin=…) - changed:
function arma_impulse_response(ar, ma, leads=…, **kwargs) → function arma_impulse_response(ar, ma, leads=…)
- changed:
function bkfilter(X, low=…, high=…, K=…) → function bkfilter(x, low=…, high=…, K=…)
- changed:
function cffilter(X, low=…, high=…, drift=…) → function cffilter(x, low=…, high=…, drift=…)
- changed:
function hpfilter(X, lamb=…) → function hpfilter(x, lamb=…)
- removed:
function cy_hamilton_filter(initial_probabilities, regime_transition, conditional_likelihoods, model_order) - removed:
function cy_kim_smoother(regime_transition, predicted_joint_probabilities, filtered_joint_probabilities) - removed:
function py_hamilton_filter(initial_probabilities, regime_transition, conditional_likelihoods, model_order) - removed:
function py_kim_smoother(regime_transition, predicted_joint_probabilities, filtered_joint_probabilities) - removed:
variable prefix_hamilton_filter_map - removed:
variable prefix_kim_smoother_map - added:
function cy_hamilton_filter_log(initial_probabilities, regime_transition, conditional_loglikelihoods, model_order) - added:
function cy_kim_smoother_log(regime_transition, predicted_joint_probabilities, filtered_joint_probabilities) - added:
property MarkovSwitchingResults.joint_likelihoods - added:
variable prefix_hamilton_filter_log_map - added:
variable prefix_kim_smoother_log_map
- removed:
variable data - removed:
variable res - removed:
variable results - removed:
variable x - changed:
constructor DecomposeResult(**kwargs) → constructor DecomposeResult(observed, seasonal, trend, resid, weights=…) - changed:
function seasonal_decompose(x, model=…, filt=…, freq=…, two_sided=…, extrapolate_trend=…) → function seasonal_decompose(x, model=…, filt=…, period=…, two_sided=…, extrapolate_trend=…) - changed:
function seasonal_mean(x, freq) → function seasonal_mean(x, period) - changed:
method DecomposeResult.plot() → method DecomposeResult.plot(observed=…, seasonal=…, trend=…, resid=…, weights=…) - added:
export STL - added:
property DecomposeResult.nobs - added:
property DecomposeResult.observed - added:
property DecomposeResult.resid - added:
property DecomposeResult.seasonal - added:
property DecomposeResult.trend - added:
property DecomposeResult.weights
- added:
export ExponentialSmoothing
- removed:
method DynamicFactorResults.get_prediction(start=…, end=…, dynamic=…, index=…, exog=…, **kwargs) - changed:
method DynamicFactor.update(params, transformed=…, complex_step=…) → method DynamicFactor.update(params, transformed=…, includes_fixed=…, complex_step=…) - added:
method DynamicFactor.clone(endog, exog=…, **kwargs) - added:
property DynamicFactor.state_names
- added:
class ExponentialSmoothing(MLEModel) - added:
class ExponentialSmoothingResults(MLEResults) - added:
class ExponentialSmoothingResultsWrapper(MLEResultsWrapper) - added:
constructor ExponentialSmoothing(endog, trend=…, damped_trend=…, seasonal=…, initialization_method=…, initial_level=…, initial_trend=…, initial_seasonal=…, bounds=…, concentrate_scale=…, dates=…, freq=…, missing=…) - added:
constructor ExponentialSmoothingResults(model, params, filter_results, cov_type=…, **kwargs) - added:
method ExponentialSmoothing.clone(endog, exog=…, **kwargs) - added:
method ExponentialSmoothing.filter(params, cov_type=…, cov_kwds=…, return_ssm=…, results_class=…, results_wrapper_class=…, *args, **kwargs) - added:
method ExponentialSmoothing.loglike(params, *args, **kwargs) - added:
method ExponentialSmoothing.smooth(params, cov_type=…, cov_kwds=…, return_ssm=…, results_class=…, results_wrapper_class=…, *args, **kwargs) - added:
method ExponentialSmoothing.transform_params(unconstrained) - added:
method ExponentialSmoothing.untransform_params(constrained) - added:
method ExponentialSmoothing.update(params, transformed=…, includes_fixed=…, complex_step=…) - added:
method ExponentialSmoothingResults.summary(alpha=…, start=…) - added:
property ExponentialSmoothing.k_params - added:
property ExponentialSmoothing.param_names - added:
property ExponentialSmoothing.start_params - added:
property ExponentialSmoothing.state_names
- removed:
field KalmanFilter.memory_no_filtered - removed:
field KalmanFilter.memory_no_forecast - removed:
field KalmanFilter.memory_no_predicted - changed:
method KalmanFilter.impulse_responses(steps=…, impulse=…, orthogonalized=…, cumulative=…, **kwargs) → method KalmanFilter.impulse_responses(steps=…, impulse=…, orthogonalized=…, cumulative=…, direct=…) - added:
field KalmanFilter.memory_no_filtered_cov - added:
field KalmanFilter.memory_no_filtered_mean - added:
field KalmanFilter.memory_no_forecast_cov - added:
field KalmanFilter.memory_no_forecast_mean - added:
field KalmanFilter.memory_no_predicted_cov - added:
field KalmanFilter.memory_no_predicted_mean - added:
method PredictionResults.clear() - added:
property KalmanFilter.memory_no_filtered - added:
property KalmanFilter.memory_no_forecast - added:
property KalmanFilter.memory_no_predicted - added:
variable MEMORY_NO_FILTERED_COV - added:
variable MEMORY_NO_FILTERED_MEAN - added:
variable MEMORY_NO_FORECAST_COV - added:
variable MEMORY_NO_FORECAST_MEAN - added:
variable MEMORY_NO_PREDICTED_COV - added:
variable MEMORY_NO_PREDICTED_MEAN
- removed:
variable unicode - changed:
method MLEModel.filter(params, transformed=…, complex_step=…, cov_type=…, cov_kwds=…, return_ssm=…, results_class=…, results_wrapper_class=…, **kwargs) → method MLEModel.filter(params, transformed=…, includes_fixed=…, complex_step=…, cov_type=…, cov_kwds=…, return_ssm=…, results_class=…, results_wrapper_class=…, low_memory=…, **kwargs) - changed:
method MLEModel.fit(start_params=…, transformed=…, cov_type=…, cov_kwds=…, method=…, maxiter=…, full_output=…, disp=…, callback=…, return_params=…, optim_score=…, optim_complex_step=…, optim_hessian=…, flags=…, **kwargs) → method MLEModel.fit(start_params=…, transformed=…, includes_fixed=…, cov_type=…, cov_kwds=…, method=…, maxiter=…, full_output=…, disp=…, callback=…, return_params=…, optim_score=…, optim_complex_step=…, optim_hessian=…, flags=…, low_memory=…, **kwargs) - changed:
method MLEModel.impulse_responses(params, steps=…, impulse=…, orthogonalized=…, cumulative=…, **kwargs) → method MLEModel.impulse_responses(params, steps=…, impulse=…, orthogonalized=…, cumulative=…, anchor=…, exog=…, extend_model=…, extend_kwargs=…, transformed=…, includes_fixed=…, **kwargs) - changed:
method MLEModel.loglikeobs(params, transformed=…, complex_step=…, **kwargs) → method MLEModel.loglikeobs(params, transformed=…, includes_fixed=…, complex_step=…, **kwargs) - changed:
method MLEModel.observed_information_matrix(params, transformed=…, approx_complex_step=…, approx_centered=…, **kwargs) → method MLEModel.observed_information_matrix(params, transformed=…, includes_fixed=…, approx_complex_step=…, approx_centered=…, **kwargs) - changed:
method MLEModel.opg_information_matrix(params, transformed=…, approx_complex_step=…, **kwargs) → method MLEModel.opg_information_matrix(params, transformed=…, includes_fixed=…, approx_complex_step=…, **kwargs) - changed:
method MLEModel.score_obs(params, method=…, transformed=…, approx_complex_step=…, approx_centered=…, **kwargs) → method MLEModel.score_obs(params, method=…, transformed=…, includes_fixed=…, approx_complex_step=…, approx_centered=…, **kwargs) - changed:
method MLEModel.simulate(params, nsimulations, measurement_shocks=…, state_shocks=…, initial_state=…) → method MLEModel.simulate(params, nsimulations, measurement_shocks=…, state_shocks=…, initial_state=…, anchor=…, repetitions=…, exog=…, extend_model=…, extend_kwargs=…, transformed=…, includes_fixed=…, **kwargs) - changed:
method MLEModel.smooth(params, transformed=…, complex_step=…, cov_type=…, cov_kwds=…, return_ssm=…, results_class=…, results_wrapper_class=…, **kwargs) → method MLEModel.smooth(params, transformed=…, includes_fixed=…, complex_step=…, cov_type=…, cov_kwds=…, return_ssm=…, results_class=…, results_wrapper_class=…, **kwargs) - changed:
method MLEModel.update(params, transformed=…, complex_step=…) → method MLEModel.update(params, transformed=…, includes_fixed=…, complex_step=…) - changed:
method MLEResults.get_prediction(start=…, end=…, dynamic=…, index=…, **kwargs) → method MLEResults.get_prediction(start=…, end=…, dynamic=…, index=…, exog=…, extend_model=…, extend_kwargs=…, **kwargs) - changed:
method MLEResults.simulate(nsimulations, measurement_shocks=…, state_shocks=…, initial_state=…) → method MLEResults.simulate(nsimulations, measurement_shocks=…, state_shocks=…, initial_state=…, anchor=…, repetitions=…, exog=…, extend_model=…, extend_kwargs=…, **kwargs) - added:
method MLEModel.clone(endog, exog=…, **kwargs) - added:
method MLEModel.fit_constrained(constraints, start_params=…, **fit_kwds) - added:
method MLEModel.fix_params(params) - added:
method MLEModel.handle_params(params, transformed=…, includes_fixed=…, return_jacobian=…) - added:
method MLEResults.aicc() - added:
method MLEResults.append(endog, exog=…, refit=…, fit_kwargs=…, **kwargs) - added:
method MLEResults.apply(endog, exog=…, refit=…, fit_kwargs=…, **kwargs) - added:
method MLEResults.extend(endog, exog=…, fit_kwargs=…, **kwargs) - added:
method MLEResults.mae() - added:
method MLEResults.mse() - added:
method MLEResults.sse() - added:
property MLEModel.state_names - added:
property MLEResults.states
- added:
method Representation.clone(endog, **kwargs) - added:
method Representation.extend(endog, start=…, end=…, **kwargs)
- removed:
method SARIMAXResults.get_prediction(start=…, end=…, dynamic=…, index=…, exog=…, **kwargs) - changed:
constructor SARIMAX(endog, exog=…, order=…, seasonal_order=…, trend=…, measurement_error=…, time_varying_regression=…, mle_regression=…, simple_differencing=…, enforce_stationarity=…, enforce_invertibility=…, hamilton_representation=…, concentrate_scale=…, **kwargs) → constructor SARIMAX(endog, exog=…, order=…, seasonal_order=…, trend=…, measurement_error=…, time_varying_regression=…, mle_regression=…, simple_differencing=…, enforce_stationarity=…, enforce_invertibility=…, hamilton_representation=…, concentrate_scale=…, trend_offset=…, use_exact_diffuse=…, dates=…, freq=…, missing=…, **kwargs) - changed:
method SARIMAX.update(params, transformed=…, complex_step=…) → method SARIMAX.update(params, transformed=…, includes_fixed=…, complex_step=…) - added:
method SARIMAX.clone(endog, exog=…, **kwargs) - added:
method SARIMAXResults.extend(endog, exog=…, **kwargs) - added:
property SARIMAX.state_names
- removed:
method UnobservedComponentsResults.get_prediction(start=…, end=…, dynamic=…, index=…, exog=…, **kwargs) - changed:
constructor UnobservedComponents(endog, level=…, trend=…, seasonal=…, freq_seasonal=…, cycle=…, autoregressive=…, exog=…, irregular=…, stochastic_level=…, stochastic_trend=…, stochastic_seasonal=…, stochastic_freq_seasonal=…, stochastic_cycle=…, damped_cycle=…, cycle_period_bounds=…, mle_regression=…, **kwargs) → constructor UnobservedComponents(endog, level=…, trend=…, seasonal=…, freq_seasonal=…, cycle=…, autoregressive=…, exog=…, irregular=…, stochastic_level=…, stochastic_trend=…, stochastic_seasonal=…, stochastic_freq_seasonal=…, stochastic_cycle=…, damped_cycle=…, cycle_period_bounds=…, mle_regression=…, use_exact_diffuse=…, **kwargs) - changed:
method UnobservedComponents.update(params, **kwargs) → method UnobservedComponents.update(params, transformed=…, includes_fixed=…, complex_step=…) - added:
method UnobservedComponents.clone(endog, exog=…, **kwargs) - added:
property UnobservedComponents.state_names
- changed:
constructor VARMAX(endog, exog=…, order=…, trend=…, error_cov_type=…, measurement_error=…, enforce_stationarity=…, enforce_invertibility=…, **kwargs) → constructor VARMAX(endog, exog=…, order=…, trend=…, error_cov_type=…, measurement_error=…, enforce_stationarity=…, enforce_invertibility=…, trend_offset=…, **kwargs) - changed:
method VARMAX.update(params, **kwargs) → method VARMAX.update(params, transformed=…, includes_fixed=…, complex_step=…) - added:
method VARMAX.clone(endog, exog=…, **kwargs) - added:
method VARMAX.simulate(params, nsimulations, measurement_shocks=…, state_shocks=…, initial_state=…, anchor=…, repetitions=…, exog=…, extend_model=…, extend_kwargs=…, transformed=…, includes_fixed=…, **kwargs) - added:
method VARMAXResults.extend(endog, exog=…, **kwargs) - added:
method VARMAXResults.simulate(nsimulations, measurement_shocks=…, state_shocks=…, initial_state=…, anchor=…, repetitions=…, exog=…, extend_model=…, extend_kwargs=…, **kwargs)
- removed:
function innovations_algo(acov, nobs=…, rtol=…) - removed:
function innovations_filter(endog, theta) - changed:
function kpss(x, regression=…, lags=…, store=…) → function kpss(x, regression=…, nlags=…, store=…) - changed:
function periodogram(X) → function periodogram(x) - added:
export innovations_algo - added:
export innovations_filter - added:
variable zivot_andrews
- added:
function freq_to_period(freq)
- removed:
class DynamicPanelVAR(DynamicVAR) - removed:
class DynamicVAR(object) - removed:
constructor DynamicPanelVAR(data, lag_order=…, window=…, window_type=…, trend=…, min_periods=…) - removed:
constructor DynamicVAR(data, lag_order=…, window=…, window_type=…, trend=…, min_periods=…) - removed:
method DynamicVAR.T() - removed:
method DynamicVAR.coefs() - removed:
method DynamicVAR.equations() - removed:
method DynamicVAR.forecast(steps=…) - removed:
method DynamicVAR.plot_forecast(steps=…, figsize=…) - removed:
method DynamicVAR.r2() - removed:
method DynamicVAR.resid() - removed:
property DynamicVAR.nobs - removed:
property DynamicVAR.result_index - removed:
variable EXPANDING - removed:
variable FULL_SAMPLE - removed:
variable ROLLING - removed:
variable data - removed:
variable var - removed:
variable var2
- changed:
class VAR(tsbase.TimeSeriesModel) → class VAR(TimeSeriesModel)
- added:
class JohansenTestResult(object) - added:
constructor JohansenTestResult(rkt, r0t, eig, evec, lr1, lr2, cvt, cvm, ind) - added:
property JohansenTestResult.cvm - added:
property JohansenTestResult.cvt - added:
property JohansenTestResult.eig - added:
property JohansenTestResult.evec - added:
property JohansenTestResult.ind - added:
property JohansenTestResult.lr1 - added:
property JohansenTestResult.lr2 - added:
property JohansenTestResult.max_eig_stat - added:
property JohansenTestResult.max_eig_stat_crit_vals - added:
property JohansenTestResult.meth - added:
property JohansenTestResult.r0t - added:
property JohansenTestResult.rkt - added:
property JohansenTestResult.trace_stat - added:
property JohansenTestResult.trace_stat_crit_vals
- changed:
function x13_arima_analysis(endog, maxorder=…, maxdiff=…, diff=…, exog=…, log=…, outlier=…, trading=…, forecast_years=…, retspec=…, speconly=…, start=…, freq=…, print_stdout=…, x12path=…, prefer_x13=…) → function x13_arima_analysis(endog, maxorder=…, maxdiff=…, diff=…, exog=…, log=…, outlier=…, trading=…, forecast_periods=…, retspec=…, speconly=…, start=…, freq=…, print_stdout=…, x12path=…, prefer_x13=…) - changed:
function x13_arima_select_order(endog, maxorder=…, maxdiff=…, diff=…, exog=…, log=…, outlier=…, trading=…, forecast_years=…, start=…, freq=…, print_stdout=…, x12path=…, prefer_x13=…) → function x13_arima_select_order(endog, maxorder=…, maxdiff=…, diff=…, exog=…, log=…, outlier=…, trading=…, forecast_periods=…, start=…, freq=…, print_stdout=…, x12path=…, prefer_x13=…)