data.form |
Convert input data into appropriate format for TANOVA |
design.matrix |
Generate design matrix for two-way factorial analysis |
F.stat |
Compute F-statistics for ANOVA model |
F.stat.null |
Generation of null F-statistics by bootstrap method |
F.stat.null2 |
Generation of null F-statistics by bootstrap method |
F.stat2 |
Compute F-statistics for ANOVA model |
fdr.table |
TANOVA False Discovery Table |
gene.classifier1 |
Classification of genes by time course analysis of variance(TANOVA) |
gene.classifier2 |
Classification of genes by time course analysis of variance(TANOVA) |
gene.classifier3 |
Classification of genes by time course analysis of variance(TANOVA) |
group.ix |
This is an internal function |
ls.estimate |
Least square estimation |
NANOVA.test |
Non-parametric analysis of variance (NANOVA) |
NANOVA.test2 |
Non-parametric analysis of variance (NANOVA) |
NANOVA.test3 |
Non-parametric analysis of variance (NANOVA) |
prior.SIGMA |
Compute the prior of covariance matrix |
prior.sigma |
Compute the prior of covariance matrix |
proj |
projection direction |
proj.data |
Projection of Raw Data |
proj.dir |
projection direction |
proj.dir2 |
projection direction |
sig.number |
The number of significant genes in the FDR table at specified quantiles |
sigma.hat |
Estimation of Covariance Matrix |
tanova |
Classification of genes by time course analysis of variance(TANOVA) |
TANOVAmanual |
Classification of genes by time course analysis of variance(TANOVA) |
trigammaInverse |
Trigamma Inverse Function |
z.score |
Z Score |