mbsts: Constructor for the MBSTS model
In mbsts: Multivariate Bayesian Structural Time Series
mbsts-class R Documentation
Constructor for the MBSTS model
Description
This class constructor build an object of MBSTS class, encoding a state space model together with a uni- or multi-variate time series, which is central to all the package's functionality. One implements the MBSTS model by specifying some or all of its basic components.
Slots
XtrainA (n*K)-dimensional matrix containing all candidate predictor series for each target series. K=∑ k_i is the number of all candidate predictors for all target series. The first k_1 variables are the set of candidate predictors for the first target series, and the next k_2 variables are the set of candidate predictors for the second target series, etc. Note that, one variable can appear in the X.star several times, since different target series can contain the same candidate predictors.
IndA (K*(mc-burn))-dimensional matrix containing MCMC draws of the indicator variable. If X.star is null, it will not be returned.
beta.hatA (K*(mc-burn))-dimensional matrix containing MCMC draws of regression coefficients. If X.star is null, it will not be returned.
B.hatA (K*m*(mc-burn))-dimensional array generated by combining beta.hat for all target series. If X.star is null, it will not be returned.
ob.sig2A (m*m*(mc-burn))-dimensional array containing MCMC draws of variance-covariance matrix for residuals.
StatesA (n*m1*(mc-burn))-dimensional array containing MCMC draws of all time series components, where m1 is the number of all time series components. If the STmodel is null, it will not be returned.
st.sig2A (K*(mc-burn))-dimensional matrix containing MCMC draws of variances for time series components. If the STmodel is null, it will not be returned.
kiA vector of integer values denoting the acumulated number of predictors for target series. For example, if there are three target series where the first has 8 predictors, the second has 6 predictors, and the third has 10 predictors, then the vector is c(8,14,24).
ntrainA numerical value for number of observations.
mtrainA numerical value for number of response variables.
Author(s)
Jinwen Qiu qjwsnow_ctw@hotmail.com Ning Ning patricianing@gmail.com
References
\Ning2021
mbsts documentation built on Jan. 7, 2023, 9:07 a.m.
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| mbsts-class | R Documentation |
Constructor for the MBSTS model
Description
This class constructor build an object of MBSTS class, encoding a state space model together with a uni- or multi-variate time series, which is central to all the package's functionality. One implements the MBSTS model by specifying some or all of its basic components.
Slots
XtrainA (n*K)-dimensional matrix containing all candidate predictor series for each target series. K=∑ k_i is the number of all candidate predictors for all target series. The first k_1 variables are the set of candidate predictors for the first target series, and the next k_2 variables are the set of candidate predictors for the second target series, etc. Note that, one variable can appear in the X.star several times, since different target series can contain the same candidate predictors.
IndA (K*(mc-burn))-dimensional matrix containing MCMC draws of the indicator variable. If X.star is null, it will not be returned.
beta.hatA (K*(mc-burn))-dimensional matrix containing MCMC draws of regression coefficients. If X.star is null, it will not be returned.
B.hatA (K*m*(mc-burn))-dimensional array generated by combining beta.hat for all target series. If X.star is null, it will not be returned.
ob.sig2A (m*m*(mc-burn))-dimensional array containing MCMC draws of variance-covariance matrix for residuals.
StatesA (n*m1*(mc-burn))-dimensional array containing MCMC draws of all time series components, where m1 is the number of all time series components. If the STmodel is null, it will not be returned.
st.sig2A (K*(mc-burn))-dimensional matrix containing MCMC draws of variances for time series components. If the STmodel is null, it will not be returned.
kiA vector of integer values denoting the acumulated number of predictors for target series. For example, if there are three target series where the first has 8 predictors, the second has 6 predictors, and the third has 10 predictors, then the vector is c(8,14,24).
ntrainA numerical value for number of observations.
mtrainA numerical value for number of response variables.
Author(s)
Jinwen Qiu qjwsnow_ctw@hotmail.com Ning Ning patricianing@gmail.com
References
\Ning2021
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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