error_minimize {findGSEP}

Minimize the Error for K-mer Frequency Fitting

Description

This function minimizes the error for k-mer frequency fitting by adjusting the mean, standard deviation, and scaling factors.

Usage

error_minimize(
  tooptimize,
  x,
  end,
  xfit,
  xfit_left,
  xfit_right,
  d,
  min_valid_pos,
  itr
)

Arguments

tooptimize

A numeric vector containing the scale factors to optimize.

x

A numeric vector representing the histogram replicated from d.

end

An integer indicating the right-side position for fitting.

xfit

x-values to get the skew normal distribution

xfit_left

A numeric value for the left-side position to calculate initial mean and standard deviation.

xfit_right

A numeric value for the right-side position to calculate initial mean and standard deviation.

d

A data frame representing the observed k-mer frequencies that will be fitted.

min_valid_pos

An integer indicating the left-side position from which the observed k-mer frequencies will be fitted.

itr

An integer representing the iteration count.

Value

A numeric value representing the minimized error.

Examples

tooptimize <- c(1, 1, 1, 1)
x <- rnorm(100)
end <- 100
xfit <- seq(min(x), max(x), length=end)
xfit_left <- min(x)
xfit_right <- max(x)
d <- data.frame(V1=1:100, V2=rnorm(100))
min_valid_pos <- 10
itr <- 100
error <- error_minimize(tooptimize, x, end, xfit, xfit_left, xfit_right, d, min_valid_pos, itr)
print(error)