View source: R/regression_utility.R
regression_utility | R Documentation |
Internal function to carry out the regression calculations.
regression_utility( data, samplelocusname, locus_id = NULL, rv, mode = NULL, logfilename, minmax, seed = 1234 )
data |
A data.table object that contains the calibration data. |
samplelocusname |
A character string. In type 1 data: locus name - name of the gene locus under investigation. In type 2 data: sample name - name of the sample under investigation. |
locus_id |
A character string. Default: NULL. ID of the respective locus (only used in type 2 correction). |
rv |
A list object. A list that contains additional objects needed for the algorithms. |
mode |
A character string. Default: NULL. Used to indicate "corrected" calibration data. |
logfilename |
A character string. Path to a file to save the log messages (default = paste0(tempdir(), "/log.txt")). |
minmax |
A logical, indicating which equations are used for BiasCorrection (default: FALSE). If TRUE, equations are used that include the respective minima and maxima of the provided data. |
seed |
A integer value. The seed used when solving the unknowns in the hyperbolic regression equation and the cubic regression equation. Important for reproducibility (default: 1234). |
The function performs the regression calculations and returns the results in a list.
# define list object to save all data rv <- list() rv$minmax <- TRUE rv$selection_method <- "RelError" rv$sample_locus_name <- "Test" rv$seed <- 1234 # define logfilename logfilename <- paste0(tempdir(), "/log.txt") # import experimental file exp_type_1 <- rBiasCorrection::example.data_experimental rv$fileimport_experimental <- exp_type_1$dat # import calibration file cal_type_1 <- rBiasCorrection::example.data_calibration rv$fileimport_calibration <- cal_type_1$dat rv$vec_cal <- cal_type_1$vec_cal # perform regression regression_results <- regression_utility( rv$fileimport_calibration, "Testlocus", locus_id = NULL, rv = rv, mode = NULL, logfilename, minmax = rv$minmax, seed = rv$seed ) length(regression_results) class(regression_results)
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