2. Average Predictive Comparisons for Models with Nonlinearity, Interactions, and Variance Components
نویسندگان
چکیده
منابع مشابه
Average Predictive Comparisons for Models with Nonlinearity, Interactions, and Variance Components
In a predictive model, what is the expected difference in the outcome associated with a unit difference in one of the inputs? In a linear regression model without interactions, this average predictive comparison is simply a regression coefficient (with associated uncertainty). In a model with nonlinearity or interactions, however, the average predictive comparison in general depends on the valu...
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In a predictive model, what is the expected change in the outcome associated with a unit change in one of the inputs? In a linear regression model without interactions, this average predictive effect is simply a regression coefficient (with associated uncertainty). In a model with nonlinearity or interactions, however, the average predictive effect in general depends on the values of the predic...
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The sample autocorrelation function (acf) of a stationary process has played a central statistical role in traditional time series analysis, where the assumption is made that the marginal distribution has a second moment. Now, the classical methods based on acf are not applicable in heavy tailed modeling. Using the codifference function as dependence measure for such processes be shown it be as...
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Extensions of the Cox proportional hazards model for survival data are studied where allowance is made for unobserved heterogeneity and for correlation between the life times of several individuals. The extendedmodels are frailty models inspired by Yashin et al. (1995). Estimation is carried out using the EM algorithm. Inference is discussed and potential applications are outlined, in particula...
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ژورنال
عنوان ژورنال: Sociological Methodology
سال: 2007
ISSN: 0081-1750,1467-9531
DOI: 10.1111/j.1467-9531.2007.00181.x