hmmat: K-Phase Design Matrix
In DBfit: A Double Bootstrap Method for Analyzing Linear Models with Autoregressive Errors
Description
Usage
Arguments
Details
References
See Also
Examples
Description
Returns the design matrix for a general k-phase intervention model
Usage
1
hmmat(vecss, k)
Arguments
vecss
a vector of length k with each element being the number of observations in each phase
k
number of phases
Details
It returns a matrix of 2*k columns. The design can be unbalanced, i.e. each phase has different observations.
References
Huitema, B. E., Mckean, J. W., & Mcknight, S. (1999). Autocorrelation effects on least-
squares intervention analysis of short time series. Educational and Psychological
Measurement, 59 (5), 767-786.
See Also
Examples
1
2
DBfit documentation built on May 1, 2021, 1:09 a.m.
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Description Usage Arguments Details References See Also Examples
Description
Returns the design matrix for a general k-phase intervention model
Usage
1 | hmmat(vecss, k)
|
Arguments
vecss |
a vector of length k with each element being the number of observations in each phase |
k |
number of phases |
Details
It returns a matrix of 2*k columns. The design can be unbalanced, i.e. each phase has different observations.
References
Huitema, B. E., Mckean, J. W., & Mcknight, S. (1999). Autocorrelation effects on least- squares intervention analysis of short time series. Educational and Psychological Measurement, 59 (5), 767-786.
See Also
Examples
1 2 |
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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