BGPsv: CI calculation for the total variance parameter in a...
In baolinwu/IPAM: Inference problems in various ANOVA models
Description
Usage
Arguments
Value
References
Description
Consider a random-effects ANOVA model, Y_{ij}=μ+u_i+ε_{ij}, where the random-effects u_i\sim N(0,σ_a^2) and
the random error components ε_{ij}\sim N(0,σ^2). We want to compute CI for the total variance parameter σ_a^2+σ^2.
An asymptotic approach and a generalized pivotal test approach are implemented. See the two references.
Usage
1
BGPsv(Y, A, alpha = 0.1, Nmax = 1e+05)
Arguments
Y
observed outcomes in an ANOVA model
A
factor level
alpha
desired significance level for the confidence interval
Nmax
total number of generalized pivotal statistics to be generated
Value
- GCI
generalized CI from Park and Burdick (2004)
- BCI
asymptotic CI from Burdick and Graybill (1984)
References
Burdick, R.K., Graybill, F.A., 1984. Confidence intervals on linear combinations of variance components in the unbalanced one-way classification. Technometrics 26, 131–136.
Park, D.J., Burdick, R.K., 2004. Confidence intervals on total variance in a regression model with an unbalanced one-fold nested error structure. Comm. Statist. Theory Methods 33, 2735–2743.
baolinwu/IPAM documentation built on May 9, 2019, 2:21 a.m.
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Description Usage Arguments Value References
Description
Consider a random-effects ANOVA model, Y_{ij}=μ+u_i+ε_{ij}, where the random-effects u_i\sim N(0,σ_a^2) and the random error components ε_{ij}\sim N(0,σ^2). We want to compute CI for the total variance parameter σ_a^2+σ^2. An asymptotic approach and a generalized pivotal test approach are implemented. See the two references.
Usage
1 | BGPsv(Y, A, alpha = 0.1, Nmax = 1e+05)
|
Arguments
Y |
observed outcomes in an ANOVA model |
A |
factor level |
alpha |
desired significance level for the confidence interval |
Nmax |
total number of generalized pivotal statistics to be generated |
Value
- GCI
generalized CI from Park and Burdick (2004)
- BCI
asymptotic CI from Burdick and Graybill (1984)
References
Burdick, R.K., Graybill, F.A., 1984. Confidence intervals on linear combinations of variance components in the unbalanced one-way classification. Technometrics 26, 131–136.
Park, D.J., Burdick, R.K., 2004. Confidence intervals on total variance in a regression model with an unbalanced one-fold nested error structure. Comm. Statist. Theory Methods 33, 2735–2743.
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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