My question is if I use randi function and say between 1 : 100, it chooses randomly a number giving equal probability to all numbers in between. Suppose I want to chose a number between 1 and 100 but give different probability for each number say proportional to the number itself.. so that 1 has a much lower probability to pick compared to 100 for e.g. how would I do that with randi function? Is that possible at all? Thanks in advance for any help.
MATLAB: How chose a number with unequal probability
matlab probability statistics
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The RAND/WBLRND functions in the Statistics Toolbox are not customizable to generic distribution functions. However, in the case of the Weibull distribution, one can analytically derive the renormalized PDF, corresponding CDF and hence a random number generator using the inverse relationship in terms of a Uniformly distributed random number.
Let's say 'ub' is the upper bound on the Weibull distribution, then the normalization factor is given by
scaleFactor = 1 - exp( (-ub/A) * 1/B );where A and B are the parameters of a regular Weibull distribution.
Following this, and using the inverse relationsip, a random number from a upper bounded Weibull Distribution is given as follows
r = A .* (-log(1 - rand(sizeOut) .* scaleFactor)) .^ (1./B);where 'sizeOut' is the number of random numbers to be generated.
One can create a custom function my modifying the file wblrnd.m and including the above two lines to generate the new values.
From the preceding discussion, it sounds like you want a model that predicts price from distance. Here is some code that will do that.
% Data
distance = [0.2 0.4 0.5 0.6]';price = [500 600 400 300]';% Fit a linear model
mdl = fitlm(distance,price);% Get predicted price over a range of distances
dq = (0 : 0.05 : 1)';pq = predict(mdl,dq);% Plot the data and the fit
figurehold onscatter(distance,price);plot(dq,pq,'r')xlabel('Distance')ylabel('Price')This code requires the Statistics and Machine Learning Toolbox. If you don't have that, you can use
[coeff] = polyfit(distance,price,1); % EDITED (to correct outputs)
to get the parameters of the linear model, and plot accordingly.
Here is the plot created by the code:
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