Trying to remove Nans when plotting histogram, pdf and cdf

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Nathaniel Porter
Nathaniel Porter 2022 年 2 月 25 日
コメント済み: Nathaniel Porter 2022 年 2 月 26 日
clear;
load InsulinReadings.mat
xX2 = InsulinReadings;
xX2(xX2==0)=missing;
A2 = mean(xX2,'all',"omitnan")
B2 = median(xX2,'all',"omitnan")
C2 = max(xX2,[],'all',"omitnan")
D2 = min(xX2,[],'all', "omitnan")
figure
histogram(InsulinReadings(~isnan(InsulinReadings),128,'Normalization')
Invalid expression. When calling a function or indexing a variable, use parentheses. Otherwise, check for mismatched delimiters.
xlabel('Insulin ng/dL')
%Now get pdf
[D PD] = allfitdist(xX2,'PDF');
xlabel('Insulin ng/dL');
%Now get the CDF
[D PD] = allfitdist(xGlucoseReadings,'CDF');
xlabel('Insulin ng/dL')

採用された回答

Voss
Voss 2022 年 2 月 25 日
I think you basically have it right. I just "fixed" a syntax error on the line where you call histogram(). ("fixed" is in quotes because I can't be sure what you're going for there.)
(Also, looks like allfitdist.m has been removed from the File Exchange, so I can't run it, but maybe your copy does the right thing here - I don't know.)
clear;
load InsulinReadings.mat
xX2 = InsulinReadings;
xX2(xX2==0)=missing;
A2 = mean(xX2,'all',"omitnan")
A2 = 296.9102
B2 = median(xX2,'all',"omitnan")
B2 = 86.4899
C2 = max(xX2,[],'all',"omitnan")
C2 = 1.0226e+04
D2 = min(xX2,[],'all', "omitnan")
D2 = 3.6900e-07
figure
histogram(InsulinReadings(~isnan(InsulinReadings)),128)%,'Normalization')
xlabel('Insulin ng/dL')
%Now get pdf
[D PD] = allfitdist(xX2,'PDF');
Unrecognized function or variable 'allfitdist'.
xlabel('Insulin ng/dL');
%Now get the CDF
[D PD] = allfitdist(xGlucoseReadings,'CDF');
xlabel('Insulin ng/dL')
  6 件のコメント
Voss
Voss 2022 年 2 月 25 日
There probably are built-in functions, but I don't know what they are off the top of my head (maybe search the documentation).
It's relatively straighforward to calculate a PDF and CDF from the properties of the histogram:
clear;
load InsulinReadings.mat
xX2 = InsulinReadings;
xX2(xX2==0)=missing;
figure();
h = histogram(xX2(~isnan(xX2)),128);%,'Normalization')
% now make a new histogram with values in the first bin replaced with NaNs
edges = get(h,'BinEdges');
xX2(xX2 < edges(2)) = NaN;
figure();
h = histogram(xX2(~isnan(xX2)),128);%,'Normalization')
xlabel('Insulin ng/dL')
% pdf and cdf
figure();
edges = get(h,'BinEdges');
counts = get(h,'BinCounts');
bin_centers = (edges(1:end-1)+edges(2:end))/2;
total_counts = sum(counts);
pdf = counts/total_counts;
cdf = cumsum(counts)/total_counts;
plot(bin_centers,pdf,'LineWidth',2);
hold on
plot(bin_centers,cdf,'LineWidth',2);
xlim(bin_centers([1 end]));
legend('PDF','CDF');
Nathaniel Porter
Nathaniel Porter 2022 年 2 月 26 日
Okay thanks

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