CV: Cross-validation statistic
In forecast: Forecasting Functions for Time Series and Linear Models
CV R Documentation
Cross-validation statistic
Description
Computes the leave-one-out cross-validation statistic (the mean of PRESS
– prediction residual sum of squares), AIC, corrected AIC, BIC and adjusted
R^2 values for a linear model.
Usage
CV(obj)
Arguments
obj
output from lm or tslm
Value
Numerical vector containing CV, AIC, AICc, BIC and AdjR2 values.
Author(s)
Rob J Hyndman
See Also
AIC
Examples
y <- ts(rnorm(120,0,3) + 20*sin(2*pi*(1:120)/12), frequency=12)
fit1 <- tslm(y ~ trend + season)
fit2 <- tslm(y ~ season)
CV(fit1)
CV(fit2)
forecast documentation built on Aug. 31, 2023, 5:13 p.m.
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| CV | R Documentation |
Cross-validation statistic
Description
Computes the leave-one-out cross-validation statistic (the mean of PRESS – prediction residual sum of squares), AIC, corrected AIC, BIC and adjusted R^2 values for a linear model.
Usage
CV(obj)
Arguments
obj |
output from |
Value
Numerical vector containing CV, AIC, AICc, BIC and AdjR2 values.
Author(s)
Rob J Hyndman
See Also
AIC
Examples
y <- ts(rnorm(120,0,3) + 20*sin(2*pi*(1:120)/12), frequency=12)
fit1 <- tslm(y ~ trend + season)
fit2 <- tslm(y ~ season)
CV(fit1)
CV(fit2)
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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