[PDF] Top 20 Bayesian Mixed Autoregressive Models
Has 3635 "Bayesian Mixed Autoregressive Models" found on our website. Below are the top 20 most common "Bayesian Mixed Autoregressive Models".
Bayesian Mixed Autoregressive Models
... time-series models with causal and noncausal components. These models are able to replicate features that previously could only be obtained by highly nonlinear and complex models, when non-gaussian ... See full document
62
Bayesian Outlier Detection in Non-Gaussian Autoregressive Time Series
... ARIMA models, Beran (1994) for Gaussian long-memory models, Chan and Cheung (1994) for threshold autoregressive models, Kleiner and Martin (1979) consider robust frequency domain ... See full document
18
Bayesian inference of mixed models in quantitative genetics of crop species
... 1971). Bayesian prediction of breeding values and genetic variances has been also largely employed (Sorensen 2009; Blasco ...and/or Bayesian inference have additional relevant applications in genetics and ... See full document
36
Ridge, Lasso and Bayesian additive-dominance genomic models
... genetics models and ...genetic models but not for additive-dominance ...predictive models (including current models and proposed modifications), fitted using Bayesian, Lasso and Ridge ... See full document
13
Bayesian analysis of autoregressive panel data model: application in genetic evaluation of beef cattle
... the models were also compared by the Pseudo- Bayes ...to models 1 and 3, even when data were simulated using model ...ries autoregressive models, and among these we refer the reader to Barreto ... See full document
9
ARTIGO_A Bayesian shrinkage approach for AMMI models
... When estimating the singular values for the AMMIB model, the estimates were shrunk rela- tive to the least squares solutions, which is consistent with the results in Crossa et al. [ 21 ] and Oliveira et al. [ 25 ]. ... See full document
27
Stevia rebaudiana (Bert) Bertoni: regression models with mixed
... regression models with mixed effects using generalized linear statistics to evaluate germination data from Stevia rebaudiana (Bert) ...linear mixed effects followed the binomial, the beta-binomial ... See full document
12
Some Bayesian generalizations of the integer-valued autoregressive model
... the autoregressive order by using a Pitman-Yor process in the distribution of the innovation rates, which entails robust results for specific choices of the process ...all models, we devised data ... See full document
83
Censored regression models with autoregressive errors = Modelos de regressão censurados com erros autorregressivos
... a Bayesian approach (c) and the last being the method proposed in his paper (d): imputing the censored values by considering the time series data as a realization from a multivariate normal distribution and then, ... See full document
76
Bayesian spatial models with a mixture neighborhood structure
... spatial Bayesian models, very few studies have considered different neighborhood structures for disease mapping ...higher autoregressive order models in the time series ... See full document
15
Bayesian prediction in threshold autoregressive models with exponential white noise
... lated since an explicit form for the support of the posterior distribution is difficult to obtain, particularly for large sample sizes. Hence, we suggest two different approaches to solve the problem. First we consider ... See full document
20
Critical points on growth curves in autoregressive and mixed models
... of models with correla- tion structure in the errors compared to models that do not consider this correlation ...sons, autoregressive models were superior to models without ... See full document
8
GARMA models, a new perspective using Bayesian methods and transformations
... Generalized autoregressive moving average (GARMA) models were devel- oped to extend the univariate Gaussian ARMA time ...such models can be applied to describe discrete time ... See full document
103
GARMA models, a new perspective using Bayesian methods and transformations
... In the Chapter 4 we propose using Box-Cox transformations in order to be able to describe our data with GARMA model. Therefore, de Andrade et al. (2016b) proposed model is TGARMA (Transformed Generalized ... See full document
103
Bayesian forecasting of temporal gene expression by using an autoregressive panel data approach
... an autoregressive panel data ...time-series models and when Poisson and negative binomial probability distributions are assumed for the gene expression ... See full document
9
Bayesian approach, traditional method, and mixed models for multienvironment trials of soybean
... the Bayesian approach (Omer et ...the Bayesian approach, was generated according to the inverse variance of 18 genotypes, collected from 55 genotypes in the present ... See full document
8
Spatial extremes of wildfire sizes: Bayesian hieralquical models for extremes
... specific models for the extremal process Y (s) to address the issue of spatial ...Similar models were already suggested by Coles and Tawn ( 1996 ) for modeling areal rainfall ...these models are ... See full document
28
Efficient bayesian methods for mixture models with genetic applications
... Unrelated to clustering, many Bayesian model-based methods for big data are variations of a strategy known as consensus Monte Carlo. Huang & Gelman (2005) suggest four alternative methods for consensus Monte ... See full document
261
Copula models for dependence: comparing classical and bayesian approaches
... Pearson’s correlation coefficient is commonly used for quantifying the intensity of linear associa- tions between two variables. Alternatively, non-parametric correlation coefficients, such as Spearman’s and Kendall’s ... See full document
134
Variance Components Estimation In Mixed Linear Models
... to mixed models with balanced data and save the unbiasedness, it does not adapt in situation with unbalanced data (mostly because it uses computations derived from fixed effect models rather than ... See full document
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