DOC: Add missing functions from the API

Add functions that are not documented in the API

Author: bashtage

docs/source/api.rst

@@ -159,7 +159,6 @@ Multivariate Models
    ~statsmodels.tsa.statespace.varmax.VARMAX
    ~statsmodels.tsa.vector_ar.svar_model.SVAR
    ~statsmodels.tsa.vector_ar.vecm.VECM
-   ~statsmodels.tsa.vector_ar.dynamic.DynamicVAR
    ~statsmodels.tsa.statespace.structural.UnobservedComponents
 
 Tools
@@ -175,6 +174,10 @@ Tools
    ~statsmodels.tsa.tsatools.lagmat
    ~statsmodels.tsa.tsatools.lagmat2ds
    ~statsmodels.tsa.seasonal.seasonal_decompose
+   ~statsmodels.tsa.seasonal.STL
+   ~statsmodels.tsa.filters.bk_filter
+   ~statsmodels.tsa.filters.cf_filter
+   ~statsmodels.tsa.filters.hp_filter
 
 Markov Switching
 ~~~~~~~~~~~~~~~~

docs/source/importpaths.rst

@@ -44,7 +44,7 @@ the namespace exploration features of IPython, Spyder, IDLE, etc.):
     'rainbow', 'rainbowplot', 'violinplot']
 
     >>> dir(sm.tsa)
-    ['AR', 'ARMA', 'DynamicVAR', 'SVAR', 'VAR', '__builtins__', '__doc__',
+    ['AR', 'ARMA', 'SVAR', 'VAR', '__builtins__', '__doc__',
     '__file__', '__name__', '__package__', 'acf', 'acovf', 'add_lag',
     'add_trend', 'adfuller', 'ccf', 'ccovf', 'datetools', 'detrend',
     'filters', 'grangercausalitytests', 'interp', 'lagmat', 'lagmat2ds',

docs/source/imputation.rst

@@ -43,6 +43,14 @@ Classes
    MICE
    MICEData
 
+.. currentmodule:: statsmodels.imputation.bayes_mi
+
+.. autosummary::
+   :toctree: generated/
+
+   MI
+   BayesGaussMI
+
 
 Implementation Details
 ----------------------

docs/source/tsa.rst

@@ -262,6 +262,7 @@ TSA Tools
 .. autosummary::
    :toctree: generated/
 
+   add_lag
    add_trend
    detrend
    lagmat

docs/source/vector_ar.rst

@@ -66,7 +66,7 @@ explicitly:
    import numpy as np
    import pandas
    import statsmodels.api as sm
-   from statsmodels.tsa.api import VAR, DynamicVAR
+   from statsmodels.tsa.api import VAR
    mdata = sm.datasets.macrodata.load_pandas().data
 
    # prepare the dates index
@@ -354,6 +354,25 @@ Reference
    NormalityTestResults
    WhitenessTestResults
 
+.. _svar:
+
+Structural Vector Autoregressions
+---------------------------------
+
+There are a matching set of classes that handle some types of Structural VAR models.
+
+.. module:: statsmodels.tsa.vector_ar.svar_model
+   :synopsis: Structural vector autoregressions and related tools
+
+.. currentmodule:: statsmodels.tsa.vector_ar.svar_model
+
+.. autosummary::
+   :toctree: generated/
+
+   SVAR
+   SVARProcess
+   SVARResults
+
 .. _vecm:
 
 Vector Error Correction Models (VECM)

statsmodels/tsa/api.py

@@ -1,5 +1,5 @@
 __all__ = ['AR', 'ARMA', 'ARIMA',
-           'var', 'VAR', 'VECM', 'SVAR', 'DynamicVAR',
+           'var', 'VAR', 'VECM', 'SVAR',
            'filters',
            'innovations',
            'tsatools',
@@ -17,7 +17,8 @@
            'SARIMAX', 'UnobservedComponents', 'VARMAX', 'DynamicFactor',
            'MarkovRegression', 'MarkovAutoregression',
            'ExponentialSmoothing', 'SimpleExpSmoothing', 'Holt',
-           'arma_generate_sample', 'ArmaProcess']
+           'arma_generate_sample', 'ArmaProcess', 'STL',
+           'bk_filter', 'cf_filter', 'hp_filter']
 
 from .ar_model import AR
 from .arima_model import ARMA, ARIMA
@@ -26,7 +27,6 @@
 from .vector_ar.var_model import VAR
 from .vector_ar.vecm import VECM
 from .vector_ar.svar_model import SVAR
-from .vector_ar.dynamic import DynamicVAR
 from .filters import api as filters
 from . import tsatools
 from .tsatools import (add_trend, detrend, lagmat, lagmat2ds, add_lag)
@@ -50,3 +50,5 @@
 from .regime_switching.markov_autoregression import MarkovAutoregression
 from .holtwinters import ExponentialSmoothing, SimpleExpSmoothing, Holt
 from .innovations import api as innovations
+from .seasonal import STL
+from .filters import bk_filter, cf_filter, hp_filter