Graphing

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Revision as of 21:29, 23 October 2015 by JL (talk | contribs) (Scatter Diagrams)
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Introduction

Line Plots

For this example we use one of Matlab's sample dataset to plot a simple line plot showing the time series movement of the stock market data. First Load the data.

load stockreturns

The data contains a (100x10) matrix of stock market observations and we are going to plot all of these data point on a single line plot using the plot function.

figure
plot(stocks(:))

Lineplot1.png

To modify an existing plot use the hold on command. Subsequent plots will then be added to the current figure. For example to add to horizontal lines indicating +/- 1 standard deviation of the stocks data:

sd=std(stocks(:);
hold on
plot(xlim, [sd sd],'--r')
plot(xlim, [-sd -sd],'--r')

Lineplot2.png

Here, in each case the plot function is plotting a straight line between two points. The first argument, xlim queries the figure to get the coordinates of the start and end of the x-axis (a two element vector), provides the x coordinates. The second argument is a vector containing the corresponding y coordinates of the two points.

The '--r' arguments specifies the plotted line to a red dashed line. Matlab supports a number of line (and marker) types of varying colours; for full details refer to Matlab's documentation on LineSpec.

Scatter Diagrams

In this example we use the wage data from the Wooldridge dataset 'wages1'


figure
scatter(educ,wage)

Scatterplot1.png


Scatter by group, in this case on gender.

gscatter(educ,wage,female,'rk','do')
xlabel('years of education')
ylabel('average hourly earnings')
legend('female','male','Location','northwest')

Scatterplot2.png

Histograms

hist(stocks(:))

Histplot1.png

figure
hist(stocks(:),40)
set(get(gca,'child'),'FaceColor','cyan','EdgeColor','blue');
title('Histogram of stock prices')

Histplot2.png

Distribution Plots

Theoretical Distributions

x=linspace(-5,5,1000);
xnorm = normpdf(x);
figure
plot(x,xnorm,'-k','LineWidth',2)
title('Probability density plot of standard Normal distribution')

TheoreticalPlot1.png


hold all
df = [1,5,10];
for ii=1:length(df)
    xt = tpdf(x,df(ii));
    plot(x,xt)
end
title('Comparing t-distributions with standard Normal')
legend('Normal','T-dist df=1','T-dist df=5','T-dist df=10')

TheoreticalPlot2.png

Observed Distributions/Kernel Density Plots