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KFAS (version 1.0.3)

Kalman Filter and Smoother for Exponential Family State Space Models.

Description

Package KFAS provides functions for Kalman filtering, smoothing, forecasting and simulation of multivariate exponential family state space models with exact diffuse initialization when distributions of some or all elements of initial state vector are unknown.

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Version

Install

install.packages('KFAS')

Monthly Downloads

27,355

Version

1.0.3

License

GPL (>= 2)

Maintainer

Jouni Helske

Last Published

March 26th, 2014

Functions in KFAS (1.0.3)

Extract Standardized Residuals from KFS output

Extract Hat Values from KFS Output

Extract Residuals of KFS output

Maximum Likelihood Estimation of a State Space Model

Extract or Replace Parts of a State Space Model

Log-likelihood of the State Space Model.

Oxford-Cambridge boat race results 1829-2000

predict.SSModel

State Space Model Predictions

KFAS: Functions for Gaussian and Non-Gaussian State Space Models

Simulation of a gaussian State Space Model

Number of males and females born in Finland from 1751 to 2011

Extracting the Partial Signal Of a State Space Model

Print SSModel Object

Mapping real valued parameters to stationary region

Extract Estimated States of State Space Model

Kalman Filter and Smoother with Exact Diffuse Initialization for Exponential Family State Space Models

Extract Fitted Values of State Space Model

Test whether object is a valid SSModel object

Linear gaussian Approximation for Non-gaussian State Space Model

Print Ouput of Kalman Filter and Smoother

Two series of average global temperature deviations for years 1880-1987

Importance Sampling of Exponential Family State Space Model

LDL Decomposition of a Matrix

Create a State Space Model Object of Class SSModel

Deviance of a State Space Model

Transform the SSModel object with multivariate observations