Point estimates: For the regression coefficients

Share:

Description

Calculates point estimates for the regression coefficient for given point estimates of the variance components 'd' and a data frame of different estimates of the heterogeneity 'h'.

Usage

1
  regressionEstimates(y, d, h_dat, x)

Arguments

y

study responses, k-vector of responses.

d

heteroscedasticity, k-vector of heteroscedasticities.

h_dat

Here, 'h_dat' should be a data frame with variables 'type' and 'h'. Thus, one may use h_dat = hEstimates(y, d, x).

x

design matrix, k-p-matrix.

Value

A list of estimates for the regression coefficients.

Here, 'h_dat' should be a data frame with variables 'type' and 'h', thus, we may use h_dat = hEstimates(y, d, x)

Examples

1
2
3
4
5
6
bcg   <- bcgVaccineData()
bcg_y <- bcg$logrisk
bcg_d <- bcg$sdiv
bcg_x <- cbind(1,bcg$x)
bcg_h <- hEstimates(y=bcg_y, d=bcg_d, x=bcg_x)
regressionEstimates(y=bcg_y, d=bcg_d, h_dat=bcg_h, x=bcg_x)

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.