Package: TSSS 1.3.4-7

Yoshinori Kawasaki

TSSS: Time Series Analysis with State Space Model

Functions for statistical analysis, modeling and simulation of time series with state space model, based on the methodology in Kitagawa (2020, ISBN: 978-0-367-18733-0).

Authors:Yoshinori Kawasaki [aut, cre], Junji Nakano [aut], Masami Saga [aut], The Institute of Statistical Mathematics [cph, fnd]

TSSS_1.3.4-7.tar.gz
TSSS_1.3.4-7.tar.gz(r-4.7-arm64)TSSS_1.3.4-7.tar.gz(r-4.7-x86_64)TSSS_1.3.4-7.tar.gz(r-4.6-arm64)TSSS_1.3.4-7.tar.gz(r-4.6-x86_64)
TSSS_1.3.4-7.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
TSSS/json (API)

# Install 'TSSS' in R:
install.packages('TSSS', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • fortran– Runtime library for GNU Fortran applications
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

fortranglibc

1.78 score 2 stars 1 scripts 623 downloads 3 mentions 32 exports 0 dependencies

Last updated from:0490ac263b. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK122
linux-devel-x86_64OK108
source / vignettesOK135
linux-release-arm64OK120
linux-release-x86_64OK113
wasm-releaseOK98

Exports:arfitarmachararmafitarmafit2boxcoxcrscorfftperklinfolsarlsar.chgptlsqrmarfitmarlsqmarspcngsimngsmthpdfuncperiodpfilterpfilterNLplot.pfilterplot.tvvarpolregprint.tvvarseasonsimssmtrendtsmoothtvartvspctvvarunicor

Dependencies:

Readme and manuals

Help Manual

Help pageTopics
Time Series Analysis with State Space ModelTSSS-package TSSS
Univariate AR Model Fittingarfit
Calculate Characteristics of Scalar ARMA Modelarmachar
Scalar ARMA Model Fittingarmafit
Scalar ARMA Model Fittingarmafit2
BLSALLFOOD DataBLSALLFOOD
Box-Cox Transformationboxcox
Cross-Covariance and Cross-Correlationcrscor
Compute a Periodogram via FFTfftper
Haibara DataHaibara
Ship's Navigation DataHAKUSAN
Kullback-Leibler Informationklinfo
Decomposition of Time Interval to Stationary Subintervalslsar
Estimation of the Change Pointlsar.chgpt
The Least Squares Method via Householder Transformationlsqr
Yule-Walker Method of Fitting Multivariate AR Modelmarfit
Least Squares Method for Multivariate AR Modelmarlsq
Cross Spectra and Power Contributionmarspc
Seismic DataMYE1F
Simulation by Non-Gaussian State Space Modelngsim
Non-Gaussian Smoothingngsmth
Nikkei225Nikkei225
The Nonlinear State-Space Model DataNLmodel
Probability Density Functionpdfunc
Compute a Periodogramperiod
Particle Filtering and Smoothingpfilter plot.pfilter
Particle Filtering and Smoothing for Nonlinear State-Space ModelpfilterNL
Sample Data for Particle Filter and SmootherPfilterSample
Plot Box-Cox Transformed Dataplot.boxcox
Plot Fitted Trigonometric Polynomialplot.lsqr
Plot Smoothed Density Functionplot.ngsmth
Plot Fitted Polynomial Trendplot.polreg
Plot Trend, Seasonal and AR Componentsplot.season
Plot Simulated Data Generated by State Space Modelplot.simulate
Plot Posterior Distribution of Smootherplot.smooth
Plot Smoothed Periodogramplot.spg
Plot Trend and Residualsplot.trend
Plot Evolutionary Power Spectra Obtained by Time Varying AR Modelplot.tvspc
Polynomial Regression Modelpolreg
Rainfall DataRainfall
Seasonal Adjustmentseason
Simulation by Gaussian State Space Modelsimssm
Sunspot Number DataSunspot
Temperatures DataTemperature
Trend Estimationtrend
Prediction and Interpolation of Time Seriestsmooth
Time Varying Coefficients AR Modeltvar
Evolutionary Power Spectra by Time Varying AR Modeltvspc
Time Varying Varianceplot.tvvar print.tvvar tvvar
Autocovariance and Autocorrelationunicor
Wholesale Hardware DataWHARD