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Dissection of X chromosome dosage compensation for quantitative traits in sheep using different statistical models. [PDF]
Sci RepGhafouri-Kesbi F, Eskandarinasab M.
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Assessment of Mother-to-Child HIV Transmission Program in Cameroon: A Three-Year Study Using Statistical Models. [PDF]
J Int Assoc Provid AIDS CareIvan MK +4 more
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Behind the scenes of cellular organization: Quantifying spatial phenotypes of puncta structures with statistical models including random fields. [PDF]
Mol Biol CellNicolaou K +4 more
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Engineering Proteins Using Statistical Models of Coevolutionary Sequence Information. [PDF]
Cold Spring Harb Perspect BiolDinan JC, McCormick JW, Reynolds KA.
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Statistics for a Diagnostic Model
Biometrics, 1961In recent years, several methods have been proposed for making medical diagnoses by machine (Ledley and Lusted [1959], Crumb and Rupe [1959]). A method devised by Brodman et al. [1959, 1960] has been used to program a high-speed electronic computer for making presumptive medical diagnoses using only information relating to the age, sex, and responses ...
van Woerkom, Adrianus J., Brodman, Keeve
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On Statistical Model Validation
Journal of Dynamic Systems, Measurement, and Control, 1996In this paper we formulate a particular statistical model validation problem in which we wish to determine the probability that a certain hypothesized parametric uncertainty model is consistent with a given input-output data record. Using a Bayesian approach and ideas from the field of hypothesis testing, we show that in many cases of interest this ...
Lee, L. H., Poolla, K.
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2019
In this chapter, we present statistical modelling approaches for predictive tasks in business and science. Most prominent is the ubiquitous multiple linear regression approach where coefficients are estimated using the ordinary least squares algorithm. There are many derivations and generalizations of that technique. In the form of logistic regression,
Dettling, Marcel, Ruckstuhl, Andreas
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In this chapter, we present statistical modelling approaches for predictive tasks in business and science. Most prominent is the ubiquitous multiple linear regression approach where coefficients are estimated using the ordinary least squares algorithm. There are many derivations and generalizations of that technique. In the form of logistic regression,
Dettling, Marcel, Ruckstuhl, Andreas
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2008
Statistical models provide an alternative approach to using dynamical models in seasonal climate forecasting. In statistical models relationships between one set of data, the predictors, and a second set, the predictands, are sought. Common predictands include seasonal mean temperatures and accumulated precipitation, and are typically predicted using ...
Mason, Simon J., Baddour, Omar
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Statistical models provide an alternative approach to using dynamical models in seasonal climate forecasting. In statistical models relationships between one set of data, the predictors, and a second set, the predictands, are sought. Common predictands include seasonal mean temperatures and accumulated precipitation, and are typically predicted using ...
Mason, Simon J., Baddour, Omar
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Statistical models and statistical inference
1981In the previous chapter we have seen how a simple statistical model can be fitted to data by estimating the unknown parameters and then making checks with residuals. After we have done this, various questions can be answered in terms of the fitted model.
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