How to estimate probabilities of an arbitrary range, based on the probability distribution of a given a data set of numbers?
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Hello,
Given a series of values x, I want to estimate the probabilities of a range of numbers U, in(using) the probability distribution of the given series x. My code works for one value, but I need probabilities of a range, Can somebody give me some feedback please?
Thank you in advance.
This is the code:
%%Generate some data/series
x=randi([-2 50],25,1);
%Values/ranges of interest
U=[-100:100];
%define histogram and probability distribution of x
h = histogram(x);
h.Normalization = 'probability';%Changing count in probabilities
h.Values(U); %finding probabilities of range U
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채택된 답변
Bruno Luong
2018년 10월 22일
편집: Bruno Luong
2018년 10월 22일
Use HISTCOUNTS then
N = histcounts(x, [-Inf, U, Inf]);
P = N(2:end) / sum(N)
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추가 답변 (2개)
Torsten
2018년 10월 22일
%%Generate some data/series
X=randi([-2 50],25,1);
%Values/ranges of interest
U=[-100:100];
X = sort(X)
[countsX, binsX] = hist(X)
cdfX = cumsum(countsX) / sum(countsX)
extrap_left = (min(U) > max(X));
extrap_right = (max(U) > max(X));
p_U_left = interp1(binsX,cdfX,min(U),'linear',extrap_left)
p_U_right = interp1(binsX,cdfX,max(U),'linear',extrap_right)
p_U = p_U_right - p_U_left
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Torsten
2018년 10월 22일
편집: Torsten
2018년 10월 22일
If you get discrete values from a random variable, say [ 1 2 4 5 6 ], how should it be possible to tell p({3}) ? (Hint: It's impossible).
In my opinion, the most reasonable estimate would be p=0 since it does not appear in the list.
If you know the distribution the values stem from, you can get a Maximum Likelihood Estimate (MLE) of the parameters describing the distribution. Having calculated these parameters, you can give estimates of probabilities for elements of your choice.
Bruno Luong
2018년 10월 22일
편집: Bruno Luong
2018년 10월 22일
not sure, is it what you want?
x=randi([-2 50],10000,1);
U=[-100:100];
h = histogram(x, U);
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