dfittool (distribution fit tool的缩写),其主要步骤如下:(1)生成数据集:点击Data弹出子菜单,子菜单中点击Data à 选择数据变量(这里选前面已输出的normrv)à Data set name 中输入数据集名à 点击Create Data Set 建立数据集 à close关闭子菜单。 (2)选择分布密度拟合:点击New Fit 弹出子菜单 à在fit name输...
Analyze Distribution Using Distribution-Specific Functions Thisexampleshowshow to usedistribution-specific functionstoperforma multistep analysisona fitted distribution. The analysis illustrates how to: Fita probability distributionto sample data that contains exam grades of 120 students by usingnormfit. Plota ...
'E2:E21'); % 回归模型的输出X1=xlsread('logistic_ex1.xlsx', 'B2:D26'); % 预测数据输入GM = fitglm(X0,Y0,'Distribution','binomial');Y1 = predict(GM,X1);N0 =1:size(Y0,1); N1= 1:size(Y1,1);plot(N0', Y0,
>> plot(x,y,'k') / 在双对数坐标下画出拟合直线 上面程序即可得到我们需要的图形，图形的再编辑可以在Figure窗口下的Edit-Figure Properties里修改（颜色、线条粗细、坐标轴命名等）。但是得注意的是，用这个plotfit函数不太能够用来拟合很复杂的函数，而只是用来拟合线性的、二维之类的，而用它来...
('Probability Density'); hold off; % 绘制CDF曲线 figure; hold on; ecdf(data); % 绘制数据的经验累积分布函数 plot(x_vals, y_cdf_vals, 'r-', 'LineWidth', 2); % 绘制CDF曲线 legend('Empirical CDF', 'Fitted Lognormal CDF'); title('Lognormal CDF Fit to Data'); xlabel('Data'); ...
Load data into a variabledata = ... % your data% Fit a gamma distribution to the datapd = fitdist(data, 'Gamma');% Generate a set of fitted values based on the gamma distributionx_fit = linspace(min(data), max(data), 733);y_fit = pdf(pd, x_fit);% Plot the ...
betafit - Beta parameter estimation. binofit - Binomial parameter estimation. dfittool - Distribution fitting tool. evfit - Extreme value parameter estimation. expfit - Exponential parameter estimation. fitdist - Distribution fitting. gamfit - Gamma parameter es 2、timation. gevfit - Generalized ...
h1 = plot([mean_val, mean_val], ylim, 'k-.', 'LineWidth', 2); % 平均值线 %h2 = plot([lower_bound, lower_bound], ylim, 'color', [0, 0.7, 0], 'Linestyle', '--', 'LineWidth', 2); % 95置信区间 %h3 = plot([upper_bound, upper_bound], ylim, 'color', [0, 0.7, 0...
functioncreateFit(arg_1,arg_2)%CREATEFITCreateplot of datasets and fits%CREATEFIT(ARG_1,ARG_2)%Createsa plot,similar to the plotinthe main distribution fitting%window,usingthe data that you provideasinput.Youcan%applythisfunction to the same data you used with dfittool%or with different data...
GM = fitglm(X0,Y0,'Distribution','binomial'); Y1 = predict(GM,X1); %% 模型的评估 N0 =1:size(Y0,1); N1= 1:size(Y1,1); plot(N0', Y0, '-kd'); hold on; scatter(N1', Y1, 'b') xlabel('数据点编号'); ylabel('输出值'); ...