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STL components of variation arise from smoothing the data using moving weighted-least-squares polynomial fitting with a moving window bandwidth in days.
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The prerequisite for FFT (removal of DC trend, cosine taper and zero padding) was applied, and Fourier amplitude spectra were calculated and smoothed using the Parzen's window of bandwidth 0.2 Hz.
Kernel densities were calculated by using Gaussian window with bandwidth selection given by Scott et al. [ 48] (R function bw.nrd).
Therefore, the ability to detect a possible cut-off in the data does not depend on any smoothing window or bandwidth.
To this end, we used a kernel density function to calculate an optimized window size (bandwidth) for dividing the genome into blocks, in which the number of genes was determined.
We also analyzed the distribution of markers along the chromosomes, by using a kernel density estimation to calculate optimal window size (bandwidth) for dividing the genome into blocks, in which we counted the number of genes.
For continuous features, the kernel density estimation [KDE; the estimate is implemented by MATLAB's "ksdensity" function, using a normal kernel function and a window parameter (bandwidth) that is a function of the number of points in the sample] [ 49] is employed to acquire the empirical probability density function f (x|E) for essential genes and f x | E ¯ for non-essential genes [ 49].
Within the Limit Reservable Bandwidth window, look under Options on the left hand side of the window.
The parameter h is called the window width or bandwidth of the kernel.
The size of this window is the bandwidth parameter for the model.
Ψ is the kernel function that must integrate to 1, and h is the window width or bandwidth of the kernel.
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