# Tagged Questions

105 views

### Pinsker's Inequality for Bayesian hypothesis testing

I am wondering if one can relate the KL divergence to the probability of error in a Bayesian binary hypothesis testing setting. That is, we have to decide between hypotheses $A$ and $B$ given ...
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### Error exponent in hypothesis testing

In hypothesis testing, one must decide between two probability distributions $P_1(x)$ and $P_2(x)$ on a finite set $X$, after observing $n$ i.i.d. samples $x_1,...,x_n$ drawn from the unknown ...
328 views

### On error probability bounds in Bayesian hypothesis testing

In the Bayesian version of (binary) hypothesis testing one has to decide which of two hypotheses $A$ and $B$ holds true. The two hypotheses are given prior probability $p(A)$ and $p(B)$, summing up to ...
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### Akaike Information Criterion and composite variables

Akaike information criterion is a measure for goodness of fit of a model that compensates for the number of parameters that were used to build that model. Consider two linear models, one that is ...
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### How does one express the decrease in minimal type II error bound for each observation added?

Problem: I have a "classifier" that uses some arbitrary hypothesis test on observations from one of two known probability distributions: $P_0$ (null hypothesis $H_0$) is a zero-mean Gaussian ...
In my research I have run into the following general problem: I have two distributions $P$ and $Q$ over the same domain, and a large (but finite) number of samples from those distributions. Samples ...