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RERs were estimated by a multivariate generalized linear model with a Poisson error structure, which was based on collapsed relative survival data, by using exact survival times.
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Data were analyzed using a multivariate generalized additive model accounting for the sampling design and the sampling weights.
In particular, we employ a multivariate generalized autoregressive conditionally heteroskedastic (MVGARCH) model involving time-varying settings and multivariate Markov switching autoregressive conditionally heteroskedastic (MVSWARCH) model with regime-switching techniques and compare them with a conventional linear regression-based (LRB) model.
In this paper, a multivariate generalized Gaussian distribution is adopted as the source prior which can exploit frequency domain energy correlation within each source vector.
Methodologically, we linked a multivariate generalized autoregressive conditional heteroscedasticity model (mGARCH (1,1)) with three global land use scenarios that are of strategic importance to the forest bioeconomy.
Therein, Lange et al. [10] proposed a multivariate generalized estimating equations (GEEs) based method, termed FBAT-GEE.
This matrix was used to specify the variance structure in a multivariate generalized linear model.
Relative excess risks of death (RER) were estimated using a multivariate generalized linear model with a Poisson distribution, based on collapsed relative survival data, using exact survival times.
A multivariate generalization of classical order statistics for random samples from a continuous multivariate distribution was defined by Corley [18].
Infliximab was associated with the lowest cost for all indications as determined by the multivariate generalized linear model.
MaAsLin tests a sparse multivariate generalized linear model against each feature independently.
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