markov-chain | Simple Scala Markov Chain | Bot library

This is in Python.

I want to write a simple Markov-Chain thingy in about 75 lines of code on my Calculator. the only Module im able to import is "Random" and "Math".

heres a quick copy i made, should work in the python terminal, where it is supposed to work.
thats the only way my calculator will have it.

I am currently trying to establish an interest rate model, where I am trying to incorporate a Markov-Chain that should represent the state of the economy, i.e. 2 states for "good" and "bad". The tricky part is that I assume that the observed interest rates (in my case monthly compounded YTM of US-Tbills) follow a CIR-process of the form, and the Markov-Chain is unobserved.

Usually this is done by using different filtering and smoothing techniques in the EM-Algorithm. Unfortunately, these tend to be quite complicated and I am really struggling to implement them manually in R. So my question would be, which R-package would be the best to get around this problem. I checked out depmixS4 and hiddenmarkov, but they don't work in my case. I would appreciate any hint. Thanks a lot!

I would like to identify the probability of an activity changes across time. Below is an example (from act1_1 to act1_16) of matrix that I was using to calculate transition probabilities between activities.

head (Activities) will return a tibble: 6 x 145

I'm new to computer security but I'm trying the same to make a toggle case attack starting from a dictionary password.

I read there that it's possible to alternate uppercase and lower case word starting from a dictionary to have all combinations (case sensitive).

I don't know what command to use and 4 now I'm stopped on standard dictionary attack

I would like to identify activity changes across time. Below is an example (from act1_1 to act1_16) of matrix that I was using to calculate transition probabilities between activities.

head (Activities) will return a tibble: 6 x 145

I have a problem with representing Arabic words after using split() function in Python. I used Arabic text as input file (you can try any Arabic source).

here is my original code I worked on it derived from here

This code generates a probability distribution psi_0_x_squared. Then performs a markov chain simulation according to this probability. This probability psi_0_x_squared is actually the probability to be at position x for energy level n=0. After moving x 1000 times according to this probability I want to generate a histogram of position x. (The position frequency)

I was porting the example of a Simple Bayesian Network via Monte Carlo Markov Chain from PyMC2 to PyMC3 and it works.
The result can be found in the following gist on GitHub in the file pymc3_rain_sprinkler_grass_simple_bayesian_network.py.

I wanted to extend the original example by providing evidence, e.g. that the grass is wet and then let PyMC3 give me the answer for questions like "given grass is wet, what is the probability that it has rained?".

It seems that the resulting trace is "constant", e.g. there is no element of randomness in it any more. Have a look at pymc3_rain_sprinkler_grass_simple_bayesian_network_with_evidence.py in the gist and execute the df.drop_duplicates() to see what I mean.

What am I doing wrong?

In this following dataset (mcve_01.txt):

mcve_01.txt