Results 241 to 250 of about 102,684 (297)

Determination of the preliminary discriminating concentration of broflanilide against malaria vector mosquito Anopheles gambiae by multi-centre susceptibility testing. [PDF]

Malar J
Ando Y, Mori K, Bradley J, Snetselaar J, Small G.   +4 more
europepmc   +1 more source

The mediation effects of smartphone addiction, negative emotion and psychological resilience in the relationship between social support and sleep quality among medical students. [PDF]

Front Psychiatry
Zhang Y, Liu M, Yu W, Gao Z, Zhao D, Yan W, Wang W, Gao X, Wang Q.   +8 more
europepmc   +1 more source

Development and validation of the Prejudice about Cesarean Birth Scale (PCBS) in a Turkish sample: a methodological study. [PDF]

BMC Pregnancy Childbirth
Bugusan Oruc S, Toksoz A, Arslan Gurcuoglu E.   +2 more
europepmc   +1 more source

Randomized goodness of fit tests [PDF]

Kybernetika, 2011
Summary: Classical goodness-of-fit tests are no longer asymptotically distributional free if parameters are estimated. For a parametric model and the maximum likelihood estimator the empirical processes with estimated parameters is asymptotically transformed into a time transformed Brownian bridge by adding an independent Gaussian process that is ...
Friedrich Liese, Bing Liu
openaire   +4 more sources

Goodness-of-Fit Tests

, 2018
Based on the substitution principle, we derive one-sample goodness-of-fit tests of Kolmogorov-Smirnov and Cramer-von Mises type, respectively. In the case of a completely specified null hypothesis, these tests are distribution-free, if the cumulative distribution function under the null is a continuous function. In the case of composite null hypotheses,
Renate L. E. P. Reniers (2622055), Adam N. Pailing (5635307)   +1 more
core   +3 more sources

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Smooth Tests of Goodness of Fit

Technometrics, 1991
AbstractSmooth tests of goodness of fit assess the fit of data to a given probability density function within a class of alternatives that differs ‘smoothly’ from the null model. These alternatives are characterized by their order: the greater the order the richer the class of alternatives. The order may be a specified constant, but data‐driven methods
Rayner, J. C. W., Thas, O., Best, D. J.
openaire   +2 more sources