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  1. P

    Monte Carlo Integration with Computationally expensive Integrant

    Consider \mathcal{R}_x = \int_{x'} C(x|x')P(x')dx', where \mathcal{R}_x = risk of following input x C(x|x') = cost of following input x when in fact input x' occured P(x') = known pdf of inputs evaluated for input x' Objective : obtain a decent estimate of the integral Challenge ...
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    estimating expected value of a difficult cost function.

    suppose i want to compute the following expectation: E = \int C(x)f(x)dx where x follows a known pdf f(x) from which we can easily draw samples, and C(x) is a function that is very difficult to compute for given x. As a result, i can not solve the integral analytically or numerically. Suppose...
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    When should a time series model be used

    Consider the following scenario: i have a set of responses y(t),y(t-1),.....y(1), where Y's are continuous and fall between [0,1] , and "t" is the time. A set of predictors x(t),x(t-1),....x(1). Some of these predictors include day of the week, month of the year, etc that "t" falls into. The...