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sns (version 1.0.0)

predict.sns: Sample-based prediction using "sns" Objects

Description

Method for sample-based prediction using the output of sns.run.

Usage

## S3 method for class 'sns':
predict(object, fpred
  , nburnin = max(nrow(object)/2, attr(object, "nnr"))
  , end = nrow(object), thin = 1, ...)
## S3 method for class 'predict.sns':
summary(object
  , quantiles = c(0.025, 0.5, 0.975)
  , ess.method = c("coda", "ise"), ...)
## S3 method for class 'summary.predict.sns':
print(x, ...)

Arguments

object
Object of class "sns" (output of sns.run) or "predict.sns" (output of predict.sns).
fpred
Prediction function, accepting a single value for the state vector and producing a vector of outputs.
nburnin
Number of burn-in iterations discarded for sample-based prediction.
end
Last iteration used in sample-based prediction.
thin
One out of thin iterations within the specified range are used for sample-based prediction.
quantiles
Values for which sample-based quantiles are calculated.
ess.method
Method used for calculating effective sample size. Default is to call effectiveSize from package coda.
x
An object of class "summary.predict.sns".
...
Arguments passed to/from other functions.

Value

  • predict.sns produces a matrix with number of rows equal to the length of prediction vector produces by fpred. Its numnber of columns is equal to the number of samples used within the user-specified range, and after thinning (if any). summary.predict.sns produces sample-based prediction mean, standard deviation, quantiles, and effective sample size.

See Also

sns, sns.run