better_model {rBiasCorrection}

better_model helper function

Description

Internal function to select the better model between hyperbolic regression and cubic regression.

Usage

better_model(
  statstable_pre,
  statstable_post_hyperbolic = NULL,
  statstable_post_cubic = NULL,
  selection_method = "SSE"
)

Arguments

statstable_pre

A data.table object, containing the output of statisticsList_() of the calculated regression parameters (form the provided calibration data).

statstable_post_hyperbolic

A data.table object, containing the output of statisticsList_() of the calculated regression parameters form the calibration data corrected with hyperbolic regression.

statstable_post_cubic

A data.table object, containing the output of statisticsList_() of the calculated regression parameters form the calibration data corrected with cubic regression.

selection_method

A character string. The method used to select the regression algorithm to correct the respective CpG site. This is by default the sum of squared errors ("SSE"). The second option is "RelError", which selects the regression method based on the theoretical relative error after correction. This metric is calculated by correcting the calibration data with both the hyperbolic regression and the cubic regression and using them again as input data to calculate the 'goodness of fit'-metrics.

Value

The function returns a data.table with 4 columns, the last column being named 'better_model', which indicates in a binary manner, if the hyperbolic model (better_model = 0) or the cubic model (better_model = 1) result in a 'better' 'SSE' or 'RelError' respectively.

Examples

# 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
)

# extract regression results
rv$result_list <- regression_results$result_list

# get regression statistics
rv$reg_stats <- statistics_list(
  rv$result_list,
  minmax = rv$minmax
)

# select the better model based on the sum of squared errrors ("SSE")
rv$choices_list <- better_model(
  statstable_pre = rv$reg_stats,
  selection_method = "SSE"
)