Search

20 Feb 2017: Tests of homogeneity, and connections to confidence intervals 10.1. Tests of homogeneity. ... Lecture 10. Tests of homogeneity, and connections to confidence intervals 2 (1–56).

20 Feb 2017: Tests of homogeneity, and connections to confidence intervals 10.1. Tests of homogeneity. ... Lecture 10. Tests of homogeneity, and connections to confidence intervals 2 (1–9).

6 Nov 2017: Identifying the functional param-eters f1,f2 from some observations in such a diffusionmodel is of fundamental importance in many appli-cations in modern science, e.g., in biology, physicsand economics. ... general, non-linear, inverse problems. In Ray

27 Sep 2017: Hisand books range over the fields of applied probabilitiy, optimization, statistics, economics, and computer science. ... He has written on problems in stochastic scheduling, Gittins index, queueing theory, large deviations, stochastic networks,

20 Feb 2017: Pearson’s Chi-squared tests. Example 9.1 continued using R:. chisq.test(n,p=ptilde). data: n. ... Goodness-of-fit of a fully-specified null distribution. Likelihood ratio tests. Pearson's Chi-squared tests.

20 Feb 2017: Pearson’s Chi-squared tests. Pearson’s Chi-squared tests. Notice that (?) and (?) are of the same form. ... Pearson’s Chi-squared tests. Example 9.1 continued using R:. chisq.test(n,p=ptilde). data: n.

8 Apr 2017: In Section 3 we explain how several RP tests can beaggregated into a single test that combines the powers of each of the tests. ... We also compare the power of RP tests to the global test procedure of Goeman et al.

21 Feb 2017: Find the form of the likelihoodratio test of H0 : θ = 1 against H1 : θ = 1.21. ... Isthe test uniformly most powerful for testing H0 : θ = θ0 against H1 : θ > θ0?

10 Mar 2017: Included Barnard, Lindley, Plackett, Armitage etc. • Barnard developed the Sequential probability ratio test’. • ... Sequential probability ratio test (SPRT). • Most powerful sequential test between two hypotheses H0 and H1. •

6 Feb 2017: It says that the most powerful test (ie the one with the smallest Type II errorprobability), among tests with size smaller than or equal to α, is the size αlikelihood ratio ... This is called a z-test. Lecture 7. Simple Hypotheses 9 (1–1).