In this paper, we develop and study a novel testing procedure that has more powerful ability to detect mean difference for functional data. general, it includes two stages: first, splitting the sample into parts selecting principle components adaptively based on first half-sample; then, constructing test statistic another half-sample. An extensive simulation is presented, which shows proposed w...

Personalized Transductive Learning (PTL) builds a unique local model for classification of each test sample and therefore is practically neighborhood dependant, i.e. a specific model is built in a subspace spanned by a set of samples adjacent to the test sample. While existing PTL methods usually define the neighborhood by a predefined (dis)similarity measure, in this paper we introduce a new c...

We continue our study of significance tests. In these notes we will introduce two new tests: one-sample t-tests and two-sample t-tests. You should pay careful attention to the fact that every test makes some assumptions about the data – often that is drawn from a normal distribution. You should also notice that all the tests follow the same pattern. It is just the computation of the test statis...

h. t-Test: This is one of the most powerful and widely used statistical tests. The ttest (Student's t) is used to calculate the confidence intervals of a measurement when the population standard deviation ()) is not know. Which is usually the case. The t-test is also used to compare two averages. The t-test corrects for the uncertainty of the sample standard deviation (s) caused by taking a sma...

We continue our study of significance tests. In these notes we will introduce two new tests: one-sample t-tests and two-sample t-tests. You should pay careful attention to the fact that every test makes some assumptions about the data – often that is drawn from a normal distribution. You should also notice that all the tests follow the same pattern. It is just the computation of the test statis...