KFAS: fitted.SSModel – R documentation

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fitted.SSModel

Smoothed Estimates or One-step-ahead Predictions of Fitted Values

Description

Computes fitted values from output of KFS (or using the SSModel object), i.e. one-step-ahead predictions f(θ[t] | y[t-1], ... , y[1]), (m) or smoothed estimates f(θ[t] | y[n], ... , y[1]), (muhat), where f is the inverse of the link function (identity in Gaussian case), except in case of Poisson distribution where f is multiplied with the exposure u[t].

Usage

## S3 method for class 'KFS'
fitted(object, start = NULL, end = NULL, filtered = FALSE, ...)

## S3 method for class 'SSModel'
fitted(object, start = NULL, end = NULL, filtered = FALSE, nsim = 0, ...)

Arguments

`object`	An object of class `KFS` or `SSModel`.
`start`	The start time of the period of interest. Defaults to first time point of the object.
`end`	The end time of the period of interest. Defaults to the last time point of the object.
`filtered`	Logical, return filtered instead of smoothed estimates of state vector. Default is `FALSE`.
`...`	Additional arguments to `KFS`. Ignored in method for object of class `KFS`.
`nsim`	Only for method for for non-Gaussian model of class `SSModel`. The number of independent samples used in importance sampling. Default is 0, which computes the approximating Gaussian model by `approxSSM` and performs the usual Gaussian filtering/smoothing so that the smoothed state estimates equals to the conditional mode of p(α[t]\|y). In case of `nsim = 0`, the mean estimates and their variances are computed using the Delta method (ignoring the covariance terms).

Value

Multivariate time series containing fitted values.

Examples

data("sexratio")
model <- SSModel(Male ~ SSMtrend(1,Q = list(NA)),u = sexratio[, "Total"],
  data = sexratio, distribution = "binomial")
model <- fitSSM(model,inits = -15, method = "BFGS")$model
out <- KFS(model)
identical(drop(out$muhat), fitted(out))

fitted(model)

KFAS

Kalman Filter and Smoother for Exponential Family State Space Models

v1.4.5

GPL (>= 2)

Authors

Jouni Helske [aut, cre] (<https://orcid.org/0000-0001-7130-793X>)

Initial release

2021-05-10