data = [/* 20个数据点的值 */]; % 计算平均值和标准差 mean_value = mean(data); std_value = std(data); % 计算t分布的临界值 t_critical = tinv(0.975, length(data)-1); % 计算置信区间 confidence_interval = t_critical * std_value / sqrt(length(data)); % 绘制数据点 plot(data, ...
plot(x, upper_bound, 'r--'); % 上置信区间折线图 plot(x, lower_bound, 'r--'); % 下置信区间折线图 hold off; % 添加图例和标题 legend('Data', '95% Confidence Interval'); title('95% Confidence Interval for the Mean of Data'); xlabel('Data Points'); ylabel('Value'); grid on...
confidence_interval = t_critical * std_value / sqrt(n); % 置信区间的宽度 % 生成x轴数据(这里假设x轴是简单的整数序列) x = 1:length(data); % 生成置信区间的上下界 upper_bound = mean_value + confidence_interval; lower_bound = mean_value - confidence_interval; % 绘制图形 figure; plot(...
在统计学中,一个概率样本的置信区间(Confidence interval)是对这个样本的某个总体参数的区间估计。置信区间展现的是这个参数的真实值有一定概率落在测量结果的周围的程度,其给出的是被测量参数的测量值的可信程度,即前面所要求的“一个概率” 。 残差在数理统计中是指实际观察值与估计值(拟合值)之间的差。 “...
I have a 100 by 3 matrix of a series and its confidence interval, what is the best way to plot this nicely in Matlab ? I apologize in advance for the somewhat loose question, if anyone knows how to specify the colors of the plot to be blue, green, green that would also be fine....
i have a signal so it's just data, that i load on Matlab and I have to plot 95% confidence interval according to student t-distribution of my signal. Exactly like photo, that i added. When i am reading some solutions about that, i am confuse because i am not good about statistics....
an R package for adding trendline and confidence interval of basic linear or nonlinear models and show equation to plot. 作者见下图。 首先安装并导入basicTrendline。 install.packages('basicTrendline') library(basicTrendline) 准备数据。 # prepare data ...
% legend('Calibration set','Validation set','Regression line','1:1 line','Confidence interval(α=0.05)'); set(gca,'Xlim',[min(x),max(x)]); set(gca,'Ylim',[min(x),max(x)]); set(gca,'FontSize',17,'Fontname', 'Times New Roman'); ...
% function: drawRibbon-Draw Ribbon Plot for Given Data (average & confidence interval)%% input paras% arrData: average data of each group; size[m(length of each group)*n(number of group);% arrConfData: confidence data of each group; size[m(length of each group)*n(number of group);...
plot(xdata,Y2+DELTA2,'b--'); plot(xdata,Y2-DELTA2,'b--'); legend('Data','Linear Fit','95% Confidence Interval'); xlabel('身高'); ylabel('腿长'); hold off; 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 4. 残差图 ...