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TSSS (version 1.2.4)

Time Series Analysis with State Space Model

Description

Functions for statistical analysis, modeling and simulation of time series with state space model, based on the methodology in Kitagawa (1993, ISBN: 4-00-007703-1 and 2005, ISBN: 4-00-005455-4).

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Version

Install

install.packages('TSSS')

Monthly Downloads

422

Version

1.2.4

License

GPL (>= 2)

Maintainer

Masami Saga

Last Published

April 22nd, 2019

Functions in TSSS (1.2.4)

Sun Spot Number Data

Temperatures Data

Wholesale Hardware Data

Least Squares Method for Multivariate AR Model

Plot Analysis Result of ARMA Model

Plot Mean Vectors of Smoother

Plot Fitted Trigonometric Polynomial

Cross Spectra and Power Contribution

The Least Squares Method via Householder Transformation

Univariate AR Model Fitting

Yule-Walker Method of Fitting Multivariate AR Model Fitting

Calculate Characteristics of Scalar ARMA Model

Plot Simulated Data Generated by State Space Model

Estimation of the Change Point

Plot Smoothed Periodogram

Time Varying Coefficients AR Model

Prediction and Interpolation of Time Series

Plot Trend, Seasonal and AR Components

Plot Trend and Residuals

Decomposition of Time Interval to Stationary Subintervals

Probability Density Function

Time Varying Variance

Seasonal Adjustment

Polynomial Regression Model

Autocovariance and Autocorrelation

Compute a Periodogram

Box-Cox Transformation

Cross-Covariance and Cross-Correlation

Simulation by Non-Gaussian State Space Model

Non-Gaussian Smoothing

Plot Evolutionary Power Spectra Obtained by Time Varying AR Model

Simulation by Gaussian State Space Model

Evolutionary Power Spectra by Time Varying AR Model

Trend Estimation

BLSALLFOOD Data

Ship's Navigation Data

Compute a Periodogram via FFT

Kullback-Leibler Information

Time Series Analysis with State Space Model

Scalar ARMA Model Fitting

Plot Smoothed Density Function

Plot Fitted Polynomial Trend