Examples of using Statistical models in English and their translations into Portuguese
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Colloquial
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Medicine
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Ecclesiastic
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Ecclesiastic
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Computer
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Official/political
These studies are structured according to the positive theory of accounting approach, where statistical models seek to measure,
Statistical models correlate to the fraction transmitted at hb(ktb) with atmospheric transmissivity(kt)
Logarithms are used for maximum-likelihood estimation of parametric statistical models. For such a model,
Nonlinear statistical models are, therefore, required to describe this behavior.
information gain when comparing statistical models of inference.
Susep and cnseg forecast insurance products of the brazilian market with statistical models.
Peirce(1877-1878) Peirce(1883) David Freedman et alia Statistics and David A. Freedman Statistical Models.
atmospheric pollution is traditionally calculated by statistical models based on the estimation of excess mortality.
The ever-growing requirements of the users of statistical data have led to discussions about the present agricultural statistical models with regard to the relationship between costs,
Consequently, they may perform better than conventional statistical models, with the advantage of being non-parametric, do not require
In statistical models were considered fixed effects of pgp
With statistical models application was possible to verify that extracts of ethanol
Anyway, carrying out three statistical models was an advantage of this study,
This analysis is done by using statistical models to define and predict normal network behavior.
Such studies require special statistical models that consider some kind of structure that support the dependence that tends to arise from the repeated measurements for the same sampling unit.
in the connection functions of the statistical models from survival analysis in the first paper to Poisson distribution with robust variance in the current paper.
Maria do Rosário Dias de Oliveira Latorre, a teacher from the Department of Epidemiology of São Paulo University's School of Public Health FSP was invited to coordinate the effort to present the most commonly used statistical models for analyzing time series.
Predictive capabilities draw on machine learning and advanced statistical models to dig automatically through enormous amounts of data,
both of which tried to reduce the sensitivity of statistical inferences to errors in formulating statistical models.
in addition of adjusting statistical models for predicting these characteristics.