cvlm: Check linear models with cross validation
In ConvFuncTimeSeries/test_t: Nonlinear time series analysis
Description
Usage
Arguments
Value
References
Description
The function checks linear models with cross-validation (out-of-sample prediction).
Usage
1
cvlm(y, x, subsize, iter = 100)
Arguments
y
dependent variable.
x
design matrix (should include constant if it is needed).
subsize
sample size of subsampling.
iter
number of iterations.
Value
The function returns a list with following components.
rmse
root mean squares of forecast errors for all iterations.
mae
mean absolute forecast errors for all iterations.
References
Tsay, R. and Chen, R. (2019). Nonlinear Time Series Analysis. Wiley, New Jersey.
ConvFuncTimeSeries/test_t documentation built on May 29, 2019, 1:39 p.m.
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Description Usage Arguments Value References
Description
The function checks linear models with cross-validation (out-of-sample prediction).
Usage
1 | cvlm(y, x, subsize, iter = 100)
|
Arguments
y |
dependent variable. |
x |
design matrix (should include constant if it is needed). |
subsize |
sample size of subsampling. |
iter |
number of iterations. |
Value
The function returns a list with following components.
rmse |
root mean squares of forecast errors for all iterations. |
mae |
mean absolute forecast errors for all iterations. |
References
Tsay, R. and Chen, R. (2019). Nonlinear Time Series Analysis. Wiley, New Jersey.
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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