Load data
Define predictor data x and response y.
load stockreturns
x = stocks(:,2:3);
y = stocks(:,1);
Perform regression (2 Predictors)
Use that data to perform a regression.
[yhat,CI] = copreg(x,y,'xpred',x,'ypred',y,'method','nested');
% ===== OUTPUT =====
Fit copula (X,Y)
Fitting Progress: 2/2
Fit copula (X)
Fitting Progress: 1/1
Case: 2-predictor
Method: nested
Regression Progress: 100.00%
Data length for fitting = 100
Data length for predicting = 100
Evaluation Results:
RMSE = 0.71676
MAPE = 5.4411
wMAPE = 0.69542
Define predictor data x and response y. Use that data to perform a regression.
load stockreturns
x = stocks(:,2:8);
y = stocks(:,1);
[yhat,CI] = copreg(x,y,'xpred',x,'ypred',y,'method','nested');
% ===== OUTPUT =====
Fit copula (X,Y)
Fitting Progress: 7/7
Fit copula (X)
Fitting Progress: 6/6
Case: 7-predictor
Method: nested
Regression Progress: 100.00%
Data length for fitting = 100
Data length for predicting = 100
Evaluation Results:
RMSE = 1.0125
MAPE = 4.134
wMAPE = 0.9
Download: this example is available on demo6.m. Visit Github
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