search for: obsv

I have a vector of values (about 8000 obs between 0 and 1). I want to display a histogram as follows: value of vector ( bw 0 and 1) | | | | | |______________________________________ all 8000 obs. So that each section of the x axis corresponds

...09 2 5.282012-03-10 2 5.102012-03-06 3 5.672012-03-07 3 7.802012-03-08 3 8.792012-03-09 3 9.432012-03-10 3 10.99 You can see, object 2 is stationary, but 3 exhibits a trend and 1 has a pulse at 3/09. What I want, in pseudo-code: flag<- list() for (i in 1:length(obsv)) { if adf.test(i) FAIL { append(flag, i) }} What I have so far: >library(tseries) >adf.test(df[which(df$ID==1), 3]) Augmented Dickey-Fuller Test data: dataDickey-Fuller = 11.1451, Lag order = 16, p-value = 0.01null hypothesis: non-stationary >adf.test(df[whi...

...),' -s 3']; model = svmtrain(train_y,train_data_best,cmd); train_pred = svmpredict(train_y,train_data_best,model); % get the predicted values for the training set I can get the train_pred, likewise I can get the test_pred (tes_pred = svmpredict(test_y,test_data_best,model);) If I have the obsved train_y,test_y and the predicted train_pred and test_pred, some statistical parameter can be calculated. But For GP, how can i get the predicted values? (from GP website: http://www.gaussianprocess.org/gpml/code/matlab/doc/) prediction: [ymu ys2 fmu fs2 ] = gp(hyp, inf, mean, cov, lik, x,...

...),' -s 3']; model = svmtrain(train_y,train_data_best,cmd); train_pred = svmpredict(train_y,train_data_best,model); % get the predicted values for the training set I can get the train_pred, likewise I can get the test_pred (tes_pred = svmpredict(test_y,test_data_best,model);) If I have the obsved train_y,test_y and the predicted train_pred and test_pred, some statistical parameter can be calculated. But For GP, how can i get the predicted values? (from GP website: http://www.gaussianprocess.org/gpml/code/matlab/doc/) prediction: [ymu ys2 fmu fs2 ] = gp(hyp, inf, mean, cov, lik, x, y...