bigfloat | Fast arbitrary precision math library | Math library

The code below compiles just fine on Windows using VC++:

I want to create a polynomial ring which has float Coefficients like this. I can create with integers but, Floats does not work.

I recently went from Julia 1.6.3 to 1.7.0. I copied the Manifest and the Project.toml files to the new environments folder and updated the Manifest file to the newer version according to instructions. Everything worked fine. However, when I later tried to add DifferentialEquations.jl I got this error:

I know in Julia I can do parse(BigFloat, x) where x might be a string or the result of readline(). However, what if I want to specify a precision to my BigFloat within the parse function?

Like you can do BigFloat(pi, precision = 50).

I believe this can be generalized to cases where you put a function, a constructor or a type into another function and you want to specify arguments of the former one.

Here is my code:

I'm having problems implementing this exercise from a quantitative economics course.

Here's my code:

I am using a third-party library in my project for BigFloat values (I used these two libraries https://github.com/Osinko/BigFloat and https://www.nuget.org/packages/BigFloat). The results I get in my machine is the wanted results; however, when I run the application in other machines (I test in 3 different machines) the application gave a different result (all three gave the same number which is different from the value I got in my machine and isn't an acceptable value for my application). I study various posts regarding different results in different machines regarding floating-point calculation, but the result produces in all the three machines were the same. So, I wonder if I am missing something. Or, how can I solve this problem?

The part of the function that does the calculation is (thisItemCount, count_system, userDuration, repairTime, MTBFValue, and workingRate values are double which I get from the user's entry via form):

I have written following code in Pluto notebook

I am using a subroutine (stats) to calculate statistics for a list of numbers. These numbers may be big enough to lose precision if stored as normal perl numbers. I recieve such numbers as JSON formatted strings. To decode these strings without losing precision, I use a JSON::PP object with allow_nonref and allow_bignum activated. I send the list of such decoded numbers to stats subroutine (see in code shown below). This routine calculates some statistics. These statistics are then encoded to JSON and saved to file.

Most of the time the process seems to work correctly, but for some inputs (see code for examples) the calculated value of mean and variance statistics are either clearly wrong, or are encoded as JSON strings by the encoder, or both. I suspect this is due to interaction of Math::BigInt and Math::BigFloat objects created by JSON decode, and List::Util::sum0.

I am trying to figure out what causes this and a way to avoid/fix this, preferably without resorting to big non core modules. I am willing to accept imprecise calculation of mean and variance, but not entirely inaccurate results or numerical results encoded as string in JSON.

A script (stats.pl) to demonstrate the problem: