Description Slots Methods Author(s) See Also Examples

The class `rcmFit`

is the output of a call to `RCMestimation`

.
It stores results from fitting a random coefficients model.

`betas`

:Object of class

`"numeric"`

. Vector of estimated global regression coefficients for each of the covariates in the design matrix.`tau2s`

:Object of class

`"numeric"`

. Vector of estimated regression coefficient variances for each of the covariates in the design matrix`X`

.`sigma2s`

:Object of class

`"numeric"`

. Vector of estimated error variances for all genes.`rho`

:Object of class

`"numeric"`

. Estimated correlation parameter between the error of two contiguous features.`av.sigma2s`

:Object of class

`"numeric"`

. Average of the unshrunken estimated error variances.`shrinkage`

:Object of class

`"numeric"`

. Applied shrinkage parameters in fitting the model.`loglik`

:Object of class

`"numeric"`

. The log-likelihood of the fitted model.`corType`

:Object of class

`"character"`

. Correlation structure of the error used.`X`

:Object of class

`"matrix"`

. The design matrix.

- .RCMloss
`signature(object = "rcmFit")`

: Calculates the log-likelihood associated with the fitted model.- RCMrandom
`signature(object = "rcmFit")`

: Samples from the distribution induced by the fitted model.- summary
`signature(object = "rcmFit")`

: Prints the estimation result.

Wessel N. van Wieringen: [email protected]

1 | ```
showClass("rcmFit")
``` |

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