Hello,
i am working on a statistical project using math.net.numerics. i would like to implement the boxcox-transform (also called power-tranform) to transform data of a specified distribution (e.g exponential) to a more normal-like distribution.
To find the best transformation paramter "lambda", i would maximize the log-likelihood function.
To see if its realy normal distributed data after the transform, i would calculate the confidence interval (e.g 95%) and if all the transformed data lies between the interval boundary, it is normal distributed data (at the moment i am using a normplot).
Is someone working on such a problem?
I have been using math.net for a while now and thougt maybe it is a functionality that would fit into the project.
it is my first time i want to support a open source project, so i hope this is the right place and way to start.
i am working on a statistical project using math.net.numerics. i would like to implement the boxcox-transform (also called power-tranform) to transform data of a specified distribution (e.g exponential) to a more normal-like distribution.
To find the best transformation paramter "lambda", i would maximize the log-likelihood function.
To see if its realy normal distributed data after the transform, i would calculate the confidence interval (e.g 95%) and if all the transformed data lies between the interval boundary, it is normal distributed data (at the moment i am using a normplot).
Is someone working on such a problem?
I have been using math.net for a while now and thougt maybe it is a functionality that would fit into the project.
it is my first time i want to support a open source project, so i hope this is the right place and way to start.