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[f,xi]=ksdensity(x); plot(xi,f) ; 概率密度是plot(xi,f)曲线的高度,它乘以底边(xi)的间距(得到面积)才是概率,当xi区间越小时,fi必然会越大,甚至于单个fi超过1。曲线下面的总面积必然为1。 a; %样本
3 A$ O) v: v1 X% a/ Hx=linspace(min(a),max(a),30); %分组7 y9 K, F8 x6 Z6 ]# j
yy=hist(a,x); %频数( y. T1 x) f7 k( r% Y9 W
bar(x,yy/length(a)); 用hist得到的是次数,它除以总的次数得到的是频率,而后者与概率的含义相同。 histfit(data); will plot the data as a histogram and show a smooth curve of the best fit gaussian to it. % 下面的还没搞清楚?? [mu, sigma] = normfit(data); pd = fitdist(data,'normal'); will give the mean (mu) and standard deviation (sigma) of that same set of data, which are used by histfit to generate the fitted curve.
$ v2 |% @1 G6 Y8 x, f5 C: {$ @ |