I am reproducing a video model. The model uses mixture-Laplacian distribution. Its probability density function is composed of low-variance Laplacian component and a high-variance Laplacian component. I want to understand what those components refer to and how to calculate them?
Hiba Ali
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I have done more research and I believe that since the variance is usually calculated as the difference between your data point(x[]) and the mean of your set of samples (mean(x)), it may make sense to think that the high-variance refers to the upper difference, i.e. x[] + mean(x). And the low-variance refers to lower difference , i.e. x[] - mean(x).
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