如何计算置信区间并将其绘制在条形图上 [英] How to compute confidence intervals and plot them on a bar plot

问题描述

如何在

data = 1x10 cell ，其中单元格中的每个值都有不同的尺寸，例如3x100、3x40、66x2等.

data = 1x10 cell , where each value in the cell has a different dimension like 3x100, 3x40, 66x2 etc.

我的目标是得到一个条形图，其中我将有10组条形，每组中每个值三个条形.在条形图上，我希望将其显示为值的中位数，并希望计算置信区间并另外显示它.

My goal is to get a bar plot, where I would have 10 group of bars and in every group three bars for each of the values. On the bar, I want it to be shown the median of the values, and I want to calculate the confidence interval and show it additionally.

在此示例中，没有一组条形图，但我的意思是向您展示我希望如何显示置信区间.在

On this example there are not group of bars, but my point is to show you how I want the confidence intervals shown. On the site, where I found this example they offer a solution where they have this command line

e1 = errorbar(mean(data), ci95);

但是我有一个问题，它找不到任何 ci95

but I have the problem that it can't find any ci95

那么，在没有安装或下载其他服务的情况下，还有其他有效的方法吗?

So, are there any other effective ways to do it, without installing or downloading additional services?

推荐答案

我发现Patrick Happel的答案不起作用，因为随后通过调用errorbar清除了图形窗口(以及变量b) .只需添加hold on命令即可解决此问题.为避免混淆，这是一个新的答案，该答案重现了Patrick的所有原始代码以及我的一些小改动:

I've found Patrick Happel's answer to not work because the figure window (and therefore the variable b) gets cleared out by subsequent calls to errorbar. Simply adding a hold on command takes care of this. To avoid confusion, here's a new answer that reproduces all of Patrick's original code, plus my small tweak:

%% Old answer
%Just to be safe, let's clear everything
clear all

data = cell(1,10);

% Random length of the data
l = randi(500, 10, 1) + 50;  

% Random "width" of the data, with 3 more likely
w = randi(4, 10, 1);
w(w==4) = 3;
% random "direction" of the data
d = randi(2, 10, 1);

% sigma of the data (in fraction of mean)
sigma = rand(10,1) / 3;

% means of the data
dmean = randi(150,10,1);
dsigma = dmean.*sigma;

for c = 1 : 10
    if d(c) == 1
        data{c} = randn(l(c), w(c)) .* dsigma(c) + dmean(c);
    else
        data{c} = randn(w(c), l(c)) .* dsigma(c) + dmean(c);
    end
end
%============================================
%Next thing is 
%    On the bar, I want it to be shown the median of the values, and I
%    want to calculate the confidence interval and show it additionally.
%
%Are you really sure you want to plot the median? The median of some data
%is not connected to the variance of the data, and hus no type of error
%bars are required. I guess you want to show the mean. If you really want
%to show the median, a box plot might be a better alternative.
%
%The following code computes and plots the mean in a bar plot:
%============================================
means = zeros(numel(data),3);
stds = zeros(numel(data),3);
n = zeros(numel(data),3);
for c = 1:numel(data)
    d = data{c};
    if size(d,1) < size(d,2)
        d = d';
    end
    cols = size(d,2);
    means(c, 1:cols) = nanmean(d);
    stds(c, 1:cols) = nanstd(d);
    n(c, 1:cols) = sum(~isnan((d)));
end

b = bar(means);

%% New code
%This ensures that b continues to reference existing data in the next for
%loop, as the graphics objects can otherwise be deleted.  
hold on
%% Continuing Patrick Happel's answer
%============================================
%Now, we need to compute the length of the error bars. Typical choices are
%the standard deviation of the data (already computed by the code above,
%stored in stds), the standard error or the 95% confidence interval (which
%is the 1.96fold of the standard error, assuming the underlying data
%follows a normal distribution).
%============================================
% for standard deviation use stds

% for standard error
ste = stds./sqrt(n);

% for 95% confidence interval
ci95 = 1.96 * ste;
%============================================
%Last thing is to plot the error bars. Here I chose the ci95 as you asked
%in your question, if you want to change that, simply change the variable
%in the call to errorbar:
%============================================
for c = 1:3
    size(means(:, c))
    size(b(c).XData)
    e = errorbar(b(c).XData + b(c).XOffset, means(:,c), ci95(:, c));
    e.LineStyle = 'none';
end

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