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These are questions asked by Teep

In LPSolve, I have solutions returned in matrix form that contain elements that are negligible (values close to zero).

Is there a simple way to convert and reduce these values to zero in the matrix (rather than return the exact values)?



Good day!

I am working to solve a double series (LP  minimization) problem of the form 

z = add(add(x[i,j]*y[i,j]*z[j], j=1..6), i=1..3).

However, this returns a set [ ]. 

Since LPSolve does not operate on a set (removing the brackets manually will enable LPSolve to obtain the solution), can anyone suggest what is wrong with the structure of this z-equation? x, y are matrices and z is a column vector.



Is there a routine available to derive the variable (i.e for any given z) for the standard normal loss function, L(z)?

If we know the value of L(z), how can z be determined?

I'm wondering if there is an available command that can evaluate the number of terms required to produce a desired outcome.

Specifically, I am interested in determining the probability of a Poisson distribution, given the parameter (mean) value and the probability outcome. I can obtain the desired result using trial and error / brute force, but I am curious to know if there is a more efficient way. 

Suppose that, lambda = 2.6 and the cumulative sum of the probabilities is 95%. I know that I must add the first 6 terms for P(x) in the series (x=0,1, ..,5) to sum to 0.95. Each term ...  P(x=0)= 0.07, P(x=1)=0.19, and so on.

However, how can we know that desired 95% outcome can be determined from the first 5 terms without trial & error?

Is there a simple command to generate decimal numbers in a given range? 

For example, I wish to obtain a randomly generated number between, say ... -0.5 and 0.5.


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