Question

我一直收到这个错误：

???指数超过矩阵维度。

==＆gt;中的错误example3_6 at 48 results = regress（cl1（trainset），   CL2（车组））; ％使用回归函数

GDX文件包含7列和386行，GLD文件包含7列和765行，但如果我从两者中取出250个样本，这应该不是问题。

有人可以告诉我这里有什么问题吗？

谢谢

clear; % make sure previously defined variables are erased.

[num, txt]=xlsread('GLD'); % read a spreadsheet named "GLD.xls" into MATLAB. 

tday1=txt(2:end, 1); % the first column (starting from the second row) is the trading days in format mm/dd/yyyy.

tday1=datestr(datenum(tday1,'mm/dd/yyyy'), 'yyyymmdd');

tday1=str2double(cellstr(tday1)); % convert the date strings first into cell arrays and then into numeric format.

adjcls1=num(:, end); % the last column contains the adjusted close prices.

[num, txt]=xlsread('GDX'); % read a spreadsheet named "GDX.xls" into MATLAB. 

tday2=txt(2:end, 1); % the first column (starting from the second row) is the trading days in format mm/dd/yyyy.

tday2=datestr(datenum(tday2,'mm/dd/yyyy'), 'yyyymmdd');

tday2=str2double(cellstr(tday2)); % convert the date strings first into cell arrays and then into numeric format.

adjcls2=num(:, end); % the last column contains the adjusted close prices.

[tday, idx1, idx2]=intersect(tday1, tday2); % find the intersection of the two data sets, and sort them in ascending order

cl1=adjcls1(idx1); 

cl2=adjcls2(idx2);  

trainset=1:252; % define indices for training set

testset=trainset(end)+1:length(tday); % define indices for test set

% determines the hedge ratio on the trainset
results=ols(cl1(trainset), cl2(trainset)); % use regression function 
hedgeRatio=results.beta;

Answer 1

您对回归功能的调用似乎有问题。

根据医生退步：

回归（y，X）返回系数估计的p-by-1向量b，用于y中对X的预测变量的响应的多线性回归.X是每个p个预测变量的n-by-p矩阵。 n个观察结果。 y是观察到的响应的n×1矢量。

但是因为我们不知道你在ols函数中如何使用回归函数，所以很难帮助你。只需对发送到regress（）的两个参数进行大小（...）检查，我相信你会发现为什么MATLAB会抱怨。

Matlab“指数超过矩阵维度。”

1 个答案: