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 creating new time series based on giving mean, standard deviation and skewness
I have a time series like

ts = [1,50,10,...,600]

I calculate the mean as

mean = 10

standard deviation = 100

skew = 5

I want to increase these parameters and then use it to generate new time series.

How can I do this in python?
As far as I understood, you want to drop the original sample and generate a new one based on
obtained values of mean, std, skew. These are only three parameters, so it is better
to know (at least) class of allowed distributions; For example, normal distribution is fully determined
by mean and std values. So, if you knew that your data came from normal distribution, it
would be sufficient to just sample from the normal distribution with specific parameters,
e.g. using numpy.random.randn.

Take a look at MCMC approach, it is usually used when needed to approximate a distribution.

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