version 0.9.0

DESCRIPTION

@@ -1,18 +1,18 @@
 Package: bsts
-Date: 2018-05-05
+Date: 2019-05-13
 Title: Bayesian Structural Time Series
 Author: Steven L. Scott <[email protected]>
 Maintainer: Steven L. Scott <[email protected]>
 Description: Time series regression using dynamic linear models fit using
  MCMC. See Scott and Varian (2014) <DOI:10.1504/IJMMNO.2014.059942>, among many
  other sources.
-Depends: BoomSpikeSlab (>= 1.0.0), zoo, xts, Boom (>= 0.8), R(>= 3.3.1)
+Depends: BoomSpikeSlab (>= 1.1.0), zoo, xts, Boom (>= 0.9), R(>= 3.4.0)
 Suggests: testthat
-LinkingTo: Boom (>= 0.8), BH (>= 1.65.0)
-Version: 0.8.0
+LinkingTo: Boom (>= 0.9), BH (>= 1.65.0)
+Version: 0.9.0
 License: LGPL-2.1 | file LICENSE
 Encoding: UTF-8
 NeedsCompilation: yes
-Packaged: 2018-05-06 14:26:29 UTC; stevescott
+Packaged: 2019-05-21 17:07:09 UTC; stevescott
 Repository: CRAN
-Date/Publication: 2018-05-07 08:59:33 UTC
+Date/Publication: 2019-05-21 22:20:15 UTC

MD5

@@ -1,33 +1,38 @@
-b955c50730d7d2bb2c5862c92c79560b *DESCRIPTION
+902ad3f6647f58dc4e2e1b9e21763e29 *DESCRIPTION
 7eb09e6fd83eb49ed22911c3b2f06744 *LICENSE
-6015ff26a0b4872c0a51c19bd36eabe1 *NAMESPACE
+6099cca41a284ee8f5e462516399ee68 *NAMESPACE
 ceb07fe9db975f5c42496dfaa33a5d14 *R/add.ar.R
-c31f07637145ebe4247e4b1947ce004e *R/add.dynamic.regression.R
+47dd0950697038f716870139c7d970e8 *R/add.dynamic.regression.R
 a2207f7a3e1753f1f3add83cc6b9dd7f *R/add.generalized.local.linear.trend.R
-1b8cdae9e7ffc77871293c68fab6f00d *R/add.local.level.R
+b774c0069c3d41ef59b59a7b4af2a651 *R/add.local.level.R
 f9d3fe80f95e42e2cc4c2444c22bfbfd *R/add.local.linear.trend.R
 f0c5dc316a9e9472ea4073a526f93ac0 *R/add.monthly.annual.cycle.R
 c55b4c89ff05f1a9c4e9fd18b7fdcc54 *R/add.random.walk.holiday.R
-914f29d1328e802f25742acf0cfdf8df *R/add.regression.holiday.R
+21e49e3ebe10ffac95c24260320a921d *R/add.regression.holiday.R
 be7dbb9f6b44ced309469e03439952ea *R/add.seasonal.R
 d4f5df46c6a15e0d4e47ede074775446 *R/add.semilocal.linear.trend.R
 f965dd362d2321286bea83acd0b40c2d *R/add.static.intercept.R
 c69a20b8a59408f1c7e47c51c180b36b *R/add.student.local.linear.trend.R
 f39fba9e5105da6b1189fe08005204fe *R/add.trig.R
-928c62a552fd093cc0cea135f2a66d22 *R/bsts.R
+b0f2197a3dbc4136b892e4aba110a690 *R/bsts.R
 642f82708acd5ce362948999df6aaf2d *R/compare.bsts.models.R
 994c84adfa23228d724050d98c6a560e *R/date.functions.R
-5fd5d060d91097904255dd91b1203993 *R/diagnostics.R
+6fe231fe1d4debe9e9edeb92eb269869 *R/diagnostics.R
+8b70727bed0ab3d005b08cfa9331a81a *R/dirm.R
 a71117be537cbee5a0abf977a519c15f *R/format.learning.data.R
-a88b58130233e6efd359b30712cb2f99 *R/format.prediction.data.R
-06527a6ef82e0eccc6bf39c38b23ffd2 *R/format.timestamps.R
-0309ec4e46317395a3b8362abf4e1c91 *R/holiday.R
+87e02726a155e84008705f0514948c35 *R/format.prediction.data.R
+eb20c475a1279437c2e7fceafb6a17cb *R/format.timestamps.R
+769da1aee699d16ed0209b0f050c111e *R/holiday.R
+3574f7ba37b5f28360e7e2b84af1c66c *R/mbsts.R
+008c684c4b718a7829ee87102e8e3045 *R/mbsts.plots.R
 c2a346a0d66201f93f85d29b01575365 *R/mixed.frequency.R
 63bc374c03e9d515b6aca12da8729631 *R/plot_seasonal_effect.R
-15eae44f2694010bf2ab4f30511726cd *R/plots.R
-27f1ae5a3eb7e48cedd54ca9b23b0a75 *R/predict.bsts.R
+5ae1e3f33d0906f21f1d951cb2c5ff3f *R/plots.R
+212f29e09d0b49f16c2bb309f4202d19 *R/predict.bsts.R
+ee2defc601d1bf213a13c42190763215 *R/predict.mbsts.R
 09187c9baabe7cdb4a0301f38b5648f1 *R/summary.bsts.R
-284c8de1cb00af502e58f2861f5a96d1 *R/utils.R
+04dc0efa0ef403afd48e252eba7e7271 *R/utils.R
+e707d635a33700be517ad31745786dc7 *data/gdp.RData
 d754a8d5f216044d2bf2d01bac709648 *data/goog.RData
 e96e68697531b9dbeffbded63b4ee8a2 *data/iclaims.RData
 258038d2808ee8a972bde78303fa0b8e *data/new.home.sales.RData
@@ -36,43 +41,59 @@ e96e68697531b9dbeffbded63b4ee8a2 *data/iclaims.RData
 761daf2618eaf1014ccc6500f3c82e61 *data/turkish.RData
 0465bac211a2e128119a6fbd17f19c56 *inst/tests/tests/testthat.R
 172df9e68c0f7876dcaade3768c2d5f9 *inst/tests/tests/testthat/test-date-range.R
+b4f9faed5df357aa818bca3b48598ffe *inst/tests/tests/testthat/test-dirm.R
+7698ef8c1adbeeaeca4036538cf2aeae *inst/tests/tests/testthat/test-dynamic-regression.R
+8e8e34dbc5a1d1735ec663091bcd03a9 *inst/tests/tests/testthat/test-holidays.R
+751344cdc3af1f935812c63ac2c29450 *inst/tests/tests/testthat/test-multivariate.R
 b8cf1c7b59eede2825f50fea5feac4c1 *inst/tests/tests/testthat/test-plot-components.R
 65a01ee43c3a462d7877d10e59dfd923 *inst/tests/tests/testthat/test-poisson.R
-63f2156e8f805114eaa562d9092f6239 *inst/tests/tests/testthat/test-regressionholiday.R
+905121aa9af3a048070013df7197dff6 *inst/tests/tests/testthat/test-prediction-errors.R
+c9cdb7f00e18460278079a78b6becc39 *inst/tests/tests/testthat/test-prediction.R
+6d0e435f602c43c1c921f580edef8b39 *inst/tests/tests/testthat/test-regressionholiday.R
 317f5cbb4b0b875a7cc3b7010ab004e8 *inst/tests/tests/testthat/test-seasonal.R
 0465bac211a2e128119a6fbd17f19c56 *inst/tests/testthat.R
 172df9e68c0f7876dcaade3768c2d5f9 *inst/tests/testthat/test-date-range.R
+b4f9faed5df357aa818bca3b48598ffe *inst/tests/testthat/test-dirm.R
+7698ef8c1adbeeaeca4036538cf2aeae *inst/tests/testthat/test-dynamic-regression.R
+8e8e34dbc5a1d1735ec663091bcd03a9 *inst/tests/testthat/test-holidays.R
+751344cdc3af1f935812c63ac2c29450 *inst/tests/testthat/test-multivariate.R
 b8cf1c7b59eede2825f50fea5feac4c1 *inst/tests/testthat/test-plot-components.R
 65a01ee43c3a462d7877d10e59dfd923 *inst/tests/testthat/test-poisson.R
-63f2156e8f805114eaa562d9092f6239 *inst/tests/testthat/test-regressionholiday.R
+905121aa9af3a048070013df7197dff6 *inst/tests/testthat/test-prediction-errors.R
+c9cdb7f00e18460278079a78b6becc39 *inst/tests/testthat/test-prediction.R
+6d0e435f602c43c1c921f580edef8b39 *inst/tests/testthat/test-regressionholiday.R
 317f5cbb4b0b875a7cc3b7010ab004e8 *inst/tests/testthat/test-seasonal.R
 65ad45f30d10d63352989bcab06c428f *man/HarveyCumulator.Rd
 7d1eef9eb650d72d09f64620466950eb *man/MATCH.NumericTimestamps.Rd
 a96603175b3b0a7b3dca2bfbe5ec5e50 *man/StateSpecification.Rd
 a863f07bc4e806e69afe473be37f2dc6 *man/SuggestBurn.Rd
 df657bb1b0399678d236648223fd97b5 *man/add.ar.Rd
-79504cafb62ae25ef0453908bea170f8 *man/add.dynamic.regression.Rd
-eee038c853a2c9ac337d1679cbaab069 *man/add.local.level.Rd
+4f63fc3d64d8769c4fa364ef89cc37d8 *man/add.dynamic.regression.Rd
+0fa2c2a977c7a55b190a8a16bf76cc2c *man/add.local.level.Rd
 58ac1422a4511ae03597045f82308c7e *man/add.local.linear.trend.Rd
-a691687535876bc69a006030667168e3 *man/add.monthly.annual.cycle.Rd
+c6aeacc25ac38af7be02246a9994d21f *man/add.monthly.annual.cycle.Rd
 3168e8a6a9d823b0ef79dd27f7caf8ef *man/add.random.walk.holiday.Rd
 3860412aa5279acee97dc3bbf9e73502 *man/add.seasonal.Rd
 ec2b5eb7a98faf7b6651e4de4bbaa9ca *man/add.semilocal.linear.trend.Rd
+fef17e124129f0e3ee01965b5e436074 *man/add.shared.local.level.Rd
 253bb74766c2d284a73fb56ec7b33fa9 *man/add.static.intercept.Rd
 b02be1b8b61962090baccf3f454fa372 *man/add.student.local.linear.trend.Rd
 dd0f4a731a23a55e13853e991fd64d2c *man/add.trig.Rd
 98e85cce5007520dfeb7e492ade2722a *man/aggregate.time.series.Rd
 bd91ad411945df7d74b054e3561cc2a6 *man/aggregate.weeks.to.months.Rd
 db4593d8299a0b801fe53df3ecd777da *man/auto.ar.Rd
-020ca56dc9ea7fb93af945333bf6ab9a *man/bsts.Rd
+7264c8a1cc321da3fac2a94a68e436e1 *man/bsts.Rd
 177c7d07d4182091f2d0b810a1dd0819 *man/bsts.options.Rd
-4c91dd057e1a7773a0374b36d7c92fb9 *man/compare.bsts.models.Rd
+2ceaadc5491d127d9021ff75b21c8e7e *man/compare.bsts.models.Rd
 99b12efa80a168f273cf27497dd8ba2b *man/date.range.Rd
 2400693969a5522e89c8306a7a5e9fe1 *man/descriptive-plots.Rd
 e1fe02375d1426b93dd3bd3489fef5fd *man/diagnostic-plots.Rd
+a5f78dc83c30bdd3316201478760be28 *man/dirm-model-options.Rd
+feecdcbc883a69f293297584f1c88f22 *man/dirm.Rd
 8d13a17d97c3769c3ebaa2e2ca3a7cce *man/estimate.time.scale.Rd
 4e1a7d996dbfc702d3790389eb8c9626 *man/extend.time.Rd
 ca6575264d7fa72e0166c23af660d9f4 *man/format.timestamps.Rd
+cb1c918fb3e17b2ecf7896dc48051a8d *man/gdp.Rd
 e7b9351ff2f8b0c117c1b2377303603d *man/geometric.sequence.Rd
 51bfcec5852936785b3662da7b902c86 *man/get.fraction.Rd
 241306175584bf65c806ddf162274936 *man/goog.Rd
@@ -81,20 +102,20 @@ e7b9351ff2f8b0c117c1b2377303603d *man/geometric.sequence.Rd
 cf7b7d18e7252f5eccd0341eb26a6d82 *man/last.day.in.month.Rd
 d001026a7f503a1d7e4c3139b193bfe5 *man/match.week.to.month.Rd
 5c321a7f4189941f9d151f71627da8d2 *man/max.window.width.Rd
-fbc9173bb7d289e7876e5cf9f31ce946 *man/mixed.frequency.Rd
+88248ff37e7a3fa6f5ba97fb96e691a2 *man/mixed.frequency.Rd
 4c9639c7bfb85396081677060adc4541 *man/month.distance.Rd
 129cf408079a8ce4c6fea7e5e1c54515 *man/named.holidays.Rd
 16d4b2b4b066dab48738e29d93bc48c7 *man/new.home.sales.Rd
-21d00209c3c667d6e98f029bc55e9a92 *man/one.step.prediction.errors.Rd
+4c46e07d7f54c2d539a6604fc6c9833d *man/one.step.prediction.errors.Rd
 58b0055a15f00de18cc481186c9de0f7 *man/plot.bsts.Rd
 4e091cfd04d4455c947e49959083e8a1 *man/plot.bsts.mixed.Rd
 6cab6053d05412eda8ea76b96595e315 *man/plot.bsts.prediction.Rd
 aebb0b01edc6c47838b60b4d211f8aed *man/plot.bsts.predictors.Rd
 e00a3f3667c8ac2aec7154523fba3211 *man/plot.holiday.Rd
-1b25e56c3037e211e20f30ae9d013b14 *man/predict.bsts.Rd
+c78ef0bf0a92aca42073a55eec89652b *man/predict.bsts.Rd
 e619692503d8decbd92a7c39b9d68327 *man/quarter.Rd
 abbc96c6de587b36dc1af2113a5845ce *man/regression.holiday.Rd
-4b1bee342b43153903ae4e0bff2164cc *man/regularize.timestamps.Rd
+c5b649ab31e29840874340433e251ccf *man/regularize.timestamps.Rd
 6b4cc84fa319b3ef0ea58b66c1389f4a *man/residuals.bsts.Rd
 16d60cbb756ab211644c86b424782865 *man/rsxfs.Rd
 380757abf616a6be77b40a4f8cbfb9d9 *man/shark.Rd
@@ -107,29 +128,48 @@ abbc96c6de587b36dc1af2113a5845ce *man/regression.holiday.Rd
 bdeeea57d63366747d7bbace634387f7 *man/turkish.Rd
 b57c602efad59be679c77a916faf619c *man/week.ends.Rd
 d96e18ecf4ab02527bf1b60ce08f106e *man/weekday.names.Rd
+cd4f3fcff595de3ac83d8e85ce89e627 *man/wide.to.long.Rd
 9ea4e3dffb7b8799efe134d1d9371acb *src/Makevars
-f0a1e4bb476ed11d20a35acc2b4381cf *src/aggregate_time_series.cc
-d1f0a31c17246042ed1cab6ef23a2e20 *src/bsts.cc
-730aacfaed3e28f453ba1ce7739ebaac *src/bsts_init.cc
-943148997af877d3b49c2e43d47265ac *src/get_date_ranges.cc
-a9f0f73d3d427db0ad37a066a924f448 *src/mixed_frequency.cc
-5773ebee74de1f882cc304d33d1a66bd *src/model_manager.cc
-3902c58e5b3343578774d63a00729ce2 *src/model_manager.h
-43debddc98f51f3555bcaf8031789092 *src/state_space_gaussian_model_manager.cc
-cd0f37caa6fefa5998007984b1429cdb *src/state_space_gaussian_model_manager.h
-fd3b2f38351bb746f95ba2bba9f42925 *src/state_space_logit_model_manager.cc
-07e3db4a0e425793fd0ec8aac24c75aa *src/state_space_logit_model_manager.h
-8325e9634756b1d1444c0fd162aca16e *src/state_space_poisson_model_manager.cc
-bf6e81dc06930563b6882b8a1d1b63d9 *src/state_space_poisson_model_manager.h
-331a1a0a57c221b6a248ca8d03b30ec6 *src/state_space_regression_model_manager.cc
-c91f632205399a21bfd1726b487789be *src/state_space_regression_model_manager.h
-96e3fd93131845ff3382b40ce9d796c9 *src/state_space_student_model_manager.cc
-c2ada5788c0717c1cf3cbde08e8e8c85 *src/state_space_student_model_manager.h
-8e692277aa776714bb61a1a7968ebb3d *src/utils.cc
-a3b730d6ef3f5f7aa453e05a12267a43 *src/utils.h
+d99ce4ef93988dc2e1b7279ab92be31e *src/aggregate_time_series.cc
+14a5789b717b958f3e2bc746f491b57d *src/bsts.cc
+bff6def51621c46b8f5024c8149e93c8 *src/bsts_init.cc
+604673026495a954489f5e86602bc48f *src/create_dynamic_intercept_state_model.cpp
+2d60cd8ba33ef34e0238517e07bf7c9c *src/create_dynamic_intercept_state_model.h
+d236648c46dbd208e54602d31214a67f *src/create_shared_state_model.cpp
+031ec35337c11a613f10c17a91068d39 *src/create_shared_state_model.h
+08bed54fdcb67b94a118ffcfd1f45ac7 *src/create_state_model.cpp
+17f6c061340e704c7cb578fcb9c4444f *src/create_state_model.h
+4a0ab82799effea8a0f2998cfb9302f7 *src/dirm.cc
+74b446972e23f99dd11f43f73a134757 *src/dynamic_intercept_model_manager.cc
+f4b47e0c03ea817b60f652813b16fb06 *src/dynamic_intercept_model_manager.h
+e6f88ebc8a3c65c29fd14268e57fe4d9 *src/get_date_ranges.cc
+fb1fc1eb0caf37cc16d259bd6fa51688 *src/mbsts.cc
+a739fc5cf1bbccb1ae83860c48992b06 *src/mixed_frequency.cc
+85796decbb76e176790f094f15337c2e *src/model_manager.cc
+40ff9e892e2c9c938555c56faa3f80de *src/model_manager.h
+5c8511a5844aed9ce31ec22c693c99df *src/multivariate_gaussian_model_manager.cc
+625e926ea16e39badcb9ad340d02aac1 *src/multivariate_gaussian_model_manager.h
+db277610eab7021c898a361d6da99b7f *src/state_space_gaussian_model_manager.cc
+2bedea75559c6e5f0a0bd7d3af6090e8 *src/state_space_gaussian_model_manager.h
+a432aebec2404eb926fe13e9bcb5fb25 *src/state_space_logit_model_manager.cc
+3f80d659d96c0f9d08cab47a32a2a9b7 *src/state_space_logit_model_manager.h
+7c476ba4d8a46e5de51c0aa2738d477d *src/state_space_poisson_model_manager.cc
+e216be891919e3263441168f35507631 *src/state_space_poisson_model_manager.h
+d12a59708f82f866ed02944f5431bb59 *src/state_space_regression_model_manager.cc
+7ac07cf5d57c124a845c31baeb64f782 *src/state_space_regression_model_manager.h
+ca0a7d4075cfcfaa3c975feae0d96249 *src/state_space_student_model_manager.cc
+70d7c3d65ab85979568d692b4a217f9f *src/state_space_student_model_manager.h
+758355f181bebfed943c020342250e5e *src/utils.cc
+fc372ceb51d515b3683b55248972d590 *src/utils.h
 0465bac211a2e128119a6fbd17f19c56 *tests/testthat.R
 172df9e68c0f7876dcaade3768c2d5f9 *tests/testthat/test-date-range.R
+fd8ee9ad4b55f92739f91279bb808452 *tests/testthat/test-dirm.R
+7698ef8c1adbeeaeca4036538cf2aeae *tests/testthat/test-dynamic-regression.R
+8e8e34dbc5a1d1735ec663091bcd03a9 *tests/testthat/test-holidays.R
+8ab76fcd982a9ba00fd8b18dc9c0ae1b *tests/testthat/test-multivariate.R
 b8cf1c7b59eede2825f50fea5feac4c1 *tests/testthat/test-plot-components.R
 65a01ee43c3a462d7877d10e59dfd923 *tests/testthat/test-poisson.R
+905121aa9af3a048070013df7197dff6 *tests/testthat/test-prediction-errors.R
+c9cdb7f00e18460278079a78b6becc39 *tests/testthat/test-prediction.R
 6d0e435f602c43c1c921f580edef8b39 *tests/testthat/test-regressionholiday.R
-317f5cbb4b0b875a7cc3b7010ab004e8 *tests/testthat/test-seasonal.R
+8282070b888b834e69ca9ba187ff864b *tests/testthat/test-seasonal.R

NAMESPACE

@@ -4,7 +4,7 @@ importFrom("grDevices", "dev.off", "gray", "pdf", "rainbow")
 
 importFrom("graphics", "abline", "axis", "axis.Date", "axis.POSIXct", "box",
  "boxplot", "hist", "legend", "lines", "par", "plot", "points",
- "polygon", "title", "close.screen", "screen", "split.screen",
+ "polygon", "text", "title", "close.screen", "screen", "split.screen",
  "strheight", "strwidth")
 
 importFrom("stats", ".checkMFClasses", ".getXlevels", "acf", "delete.response",
@@ -28,6 +28,7 @@ export(AcfDist,
  AddRegressionHoliday,
  AddSeasonal,
  AddSemilocalLinearTrend,
+ AddSharedLocalLevel,
  AddStaticIntercept,
  AddStudentLocalLinearTrend,
  AddTrig,
@@ -42,6 +43,11 @@ export(AcfDist,
  DateRangeHoliday,
  DateToPOSIX,
  DayPlot,
+ dirm,
+ DirmModelOptions,
+ DynamicRegressionArOptions,
+ DynamicRegressionHierarchicalRandomWalkOptions,
+ DynamicRegressionRandomWalkOptions,
  EstimateTimeScale,
  ExtendTime,
  FixedDateHoliday,
@@ -53,11 +59,13 @@ export(AcfDist,
  IsRegular,
  LastDayInMonth,
  LastWeekdayInMonthHoliday,
+ LongToWide,
  MATCH.NumericTimestamps,
  MatchWeekToMonth,
  MaxWindowWidth,
  MaxWindowWidth.default,
  MaxWindowWidth.DateRangeHoliday,
+# mbsts,
  MonthDistance,
  MonthPlot,
  NamedHoliday,
@@ -99,6 +107,7 @@ export(AcfDist,
  weekday.names,
  WeekEndsMonth,
  WeekEndsQuarter,
+ WideToLong,
  YearMonToPOSIX,
  YearPlot)
 
@@ -110,6 +119,9 @@ S3method(residuals, bsts)
 S3method(plot, bsts.prediction)
 S3method(plot, bsts.mixed)
 
+#S3method(plot, mbsts)
+#S3method(predict, mbsts)
+
 # Plot methods for specific state components
 S3method(plot, StateModel)
 S3method(plot, HierarchicalRegressionHolidayStateModel)