21 resultados para Bayesian inference on precipitation
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo
Resumo:
The circumscription of genera belonging to tribe Bignonieae (Bignoniaceae) has traditionally been complex, with only a few genera having stable circumscriptions in the various classification systems proposed for the tribe. The genus Lundia, for instance, is well characterized by a series of morphological synapomorphies and its circumscription has remained quite stable throughout its history. Despite the stable circumscription of Lundia, the circumscription of species within the genus has remained problematic. This study aims to reconstruct the phylogeny of Lundia in order to refine species circumscriptions, gain a better understanding of relationships between taxa, and identify potential morphological synapomorphies for species and major clades. We sampled 26 accessions representing 13 species of Lundia, and 5 outgroups, and reconstructed the phylogeny of the genus using a chloroplast (ndhF) and a nuclear marker (PepC). Data derived from sequences of the individual loci were analyzed using parsimony and Bayesian inference, and the combined molecular dataset was analyzed with Bayesian methods. The monophyly of Lundia nitidula, a species with a particularly complex circumscription, was tested using Shimodaira-Hasegawa (SH) test and the approximately unbiased test for phylogenetic tree selection (AU test). In addition, 40 morphological characters were mapped onto the tree that resulted from the analysis of the combined molecular dataset in order to identify morphological synapomorphies of individual species and major clades. Lundia and most species currently recognized within the genus were strongly supported as monophyletic in all analyses. One species, Lundia nitidula, was not resolved as monophyletic, but the monophyly of this species was not rejected by the AU and SH tests. Lundia sect. Eriolundia is resolved as paraphyletic in all analyses, while Lundia sect. Eulundia is monophyletic and supported by the same morphological characters traditionally used to circumscribe this section. The phylogeny of Lundia contributed important information for a better circumscription of species and served as basis the taxonomic revision of the genus.
Resumo:
A data set of a commercial Nellore beef cattle selection program was used to compare breeding models that assumed or not markers effects to estimate the breeding values, when a reduced number of animals have phenotypic, genotypic and pedigree information available. This herd complete data set was composed of 83,404 animals measured for weaning weight (WW), post-weaning gain (PWG), scrotal circumference (SC) and muscle score (MS), corresponding to 116,652 animals in the relationship matrix. Single trait analyses were performed by MTDFREML software to estimate fixed and random effects solutions using this complete data. The additive effects estimated were assumed as the reference breeding values for those animals. The individual observed phenotype of each trait was adjusted for fixed and random effects solutions, except for direct additive effects. The adjusted phenotype composed of the additive and residual parts of observed phenotype was used as dependent variable for models' comparison. Among all measured animals of this herd, only 3160 animals were genotyped for 106 SNP markers. Three models were compared in terms of changes on animals' rank, global fit and predictive ability. Model 1 included only polygenic effects, model 2 included only markers effects and model 3 included both polygenic and markers effects. Bayesian inference via Markov chain Monte Carlo methods performed by TM software was used to analyze the data for model comparison. Two different priors were adopted for markers effects in models 2 and 3, the first prior assumed was a uniform distribution (U) and, as a second prior, was assumed that markers effects were distributed as normal (N). Higher rank correlation coefficients were observed for models 3_U and 3_N, indicating a greater similarity of these models animals' rank and the rank based on the reference breeding values. Model 3_N presented a better global fit, as demonstrated by its low DIC. The best models in terms of predictive ability were models 1 and 3_N. Differences due prior assumed to markers effects in models 2 and 3 could be attributed to the better ability of normal prior in handle with collinear effects. The models 2_U and 2_N presented the worst performance, indicating that this small set of markers should not be used to genetically evaluate animals with no data, since its predictive ability is restricted. In conclusion, model 3_N presented a slight superiority when a reduce number of animals have phenotypic, genotypic and pedigree information. It could be attributed to the variation retained by markers and polygenic effects assumed together and the normal prior assumed to markers effects, that deals better with the collinearity between markers. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.
Resumo:
To estimate causal relationships, time series econometricians must be aware of spurious correlation, a problem first mentioned by Yule (1926). To deal with this problem, one can work either with differenced series or multivariate models: VAR (VEC or VECM) models. These models usually include at least one cointegration relation. Although the Bayesian literature on VAR/VEC is quite advanced, Bauwens et al. (1999) highlighted that "the topic of selecting the cointegrating rank has not yet given very useful and convincing results". The present article applies the Full Bayesian Significance Test (FBST), especially designed to deal with sharp hypotheses, to cointegration rank selection tests in VECM time series models. It shows the FBST implementation using both simulated and available (in the literature) data sets. As illustration, standard non informative priors are used.
Resumo:
In this article, we propose a new Bayesian flexible cure rate survival model, which generalises the stochastic model of Klebanov et al. [Klebanov LB, Rachev ST and Yakovlev AY. A stochastic-model of radiation carcinogenesis - latent time distributions and their properties. Math Biosci 1993; 113: 51-75], and has much in common with the destructive model formulated by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)]. In our approach, the accumulated number of lesions or altered cells follows a compound weighted Poisson distribution. This model is more flexible than the promotion time cure model in terms of dispersion. Moreover, it possesses an interesting and realistic interpretation of the biological mechanism of the occurrence of the event of interest as it includes a destructive process of tumour cells after an initial treatment or the capacity of an individual exposed to irradiation to repair altered cells that results in cancer induction. In other words, what is recorded is only the damaged portion of the original number of altered cells not eliminated by the treatment or repaired by the repair system of an individual. Markov Chain Monte Carlo (MCMC) methods are then used to develop Bayesian inference for the proposed model. Also, some discussions on the model selection and an illustration with a cutaneous melanoma data set analysed by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)] are presented.
Resumo:
The sediments resulting of natural or anthropic erosion are deposited on the soil surface and around the trunks of trees occurring in riparian forests. For assessment of the erosion, tree-rings of roots and stems were analyzed. Guarea guidonea trees from a riparian forest affected by the sedimentation of soil erosion from pastures and soybean fields in state of Goias were selected. Wood samples were extracted through a non-destructive method at three heights from trunks of trees located in three positions (top, middle and bottom) of a riparian slope. The evaluation revealed a deposition of a thick sediment layer up to 34 cm around the base of tree trunks during the past 24 years. The inter-correlations between the tree-rings widths present in wood samples at the base and at 50 and 100 cm from Guarea guidonea tree trunks presented low, medium and high values. These values resulted from the low tree-rings distinctiveness in the wood; the absence of some rings as well as the eccentricity of the pith. The analyses of dendrogeomorphology allowed the determination of the date of seed germination and tree growth and inference on the periods of sediment deposition in the trunk of the trees.
Resumo:
In this paper we propose a hybrid hazard regression model with threshold stress which includes the proportional hazards and the accelerated failure time models as particular cases. To express the behavior of lifetimes the generalized-gamma distribution is assumed and an inverse power law model with a threshold stress is considered. For parameter estimation we develop a sampling-based posterior inference procedure based on Markov Chain Monte Carlo techniques. We assume proper but vague priors for the parameters of interest. A simulation study investigates the frequentist properties of the proposed estimators obtained under the assumption of vague priors. Further, some discussions on model selection criteria are given. The methodology is illustrated on simulated and real lifetime data set.
Resumo:
Background: Arboviral diseases are major global public health threats. Yet, our understanding of infection risk factors is, with a few exceptions, considerably limited. A crucial shortcoming is the widespread use of analytical methods generally not suited for observational data - particularly null hypothesis-testing (NHT) and step-wise regression (SWR). Using Mayaro virus (MAYV) as a case study, here we compare information theory-based multimodel inference (MMI) with conventional analyses for arboviral infection risk factor assessment. Methodology/Principal Findings: A cross-sectional survey of anti-MAYV antibodies revealed 44% prevalence (n = 270 subjects) in a central Amazon rural settlement. NHT suggested that residents of village-like household clusters and those using closed toilet/latrines were at higher risk, while living in non-village-like areas, using bednets, and owning fowl, pigs or dogs were protective. The "minimum adequate" SWR model retained only residence area and bednet use. Using MMI, we identified relevant covariates, quantified their relative importance, and estimated effect-sizes (beta +/- SE) on which to base inference. Residence area (beta(Village) = 2.93 +/- 0.41; beta(Upland) = -0.56 +/- 0.33, beta(Riverbanks) = -2.37 +/- 0.55) and bednet use (beta = -0.95 +/- 0.28) were the most important factors, followed by crop-plot ownership (beta = 0.39 +/- 0.22) and regular use of a closed toilet/latrine (beta = 0.19 +/- 0.13); domestic animals had insignificant protective effects and were relatively unimportant. The SWR model ranked fifth among the 128 models in the final MMI set. Conclusions/Significance: Our analyses illustrate how MMI can enhance inference on infection risk factors when compared with NHT or SWR. MMI indicates that forest crop-plot workers are likely exposed to typical MAYV cycles maintained by diurnal, forest dwelling vectors; however, MAYV might also be circulating in nocturnal, domestic-peridomestic cycles in village-like areas. This suggests either a vector shift (synanthropic mosquitoes vectoring MAYV) or a habitat/habits shift (classical MAYV vectors adapting to densely populated landscapes and nocturnal biting); any such ecological/adaptive novelty could increase the likelihood of MAYV emergence in Amazonia.
Resumo:
The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
The gecko genus Phyllopezus occurs across South America's open biomes: Cerrado, Seasonally Dry Tropical Forests (SDTF, including Caatinga), and Chaco. We generated a multi-gene dataset and estimated phylogenetic relationships among described Phyllopezus taxa and related species. We included exemplars from both described Phyllopezus pollicaris subspecies, P. p. pollicaris and P. p. przewalskii. Phylogenies from the concatenated data as well as species trees constructed from individual gene trees were largely congruent. All phylogeny reconstruction methods showed Bogertia lutzae as the sister species of Phyllopezus maranjonensis, rendering Phyllopezus paraphyletic. We synonymized the monotypic genus Bogertia with Phyllopezus to maintain a taxonomy that is isomorphic with phylogenetic history. We recovered multiple, deeply divergent, cryptic lineages within P. pollicaris. These cryptic lineages possessed mtDNA distances equivalent to distances among other gekkotan sister taxa. Described P. pollicaris subspecies are not reciprocally monophyletic and current subspecific taxonomy does not accurately reflect evolutionary relationships among cryptic lineages. We highlight the conservation significance of these results in light of the ongoing habitat loss in South America's open biomes. (C) 2011 Elsevier Inc. All rights reserved.
Weibull and generalised exponential overdispersion models with an application to ozone air pollution
Resumo:
We consider the problem of estimating the mean and variance of the time between occurrences of an event of interest (inter-occurrences times) where some forms of dependence between two consecutive time intervals are allowed. Two basic density functions are taken into account. They are the Weibull and the generalised exponential density functions. In order to capture the dependence between two consecutive inter-occurrences times, we assume that either the shape and/or the scale parameters of the two density functions are given by auto-regressive models. The expressions for the mean and variance of the inter-occurrences times are presented. The models are applied to the ozone data from two regions of Mexico City. The estimation of the parameters is performed using a Bayesian point of view via Markov chain Monte Carlo (MCMC) methods.
Resumo:
Documenting the Neotropical amphibian diversity has become a major challenge facing the threat of global climate change and the pace of environmental alteration. Recent molecular phylogenetic studies have revealed that the actual number of species in South American tropical forests is largely underestimated, but also that many lineages are millions of years old. The genera Phyzelaphryne (1 sp.) and Adelophryne (6 spp.), which compose the subfamily Phyzelaphryninae, include poorly documented, secretive, and minute frogs with an unusual distribution pattern that encompasses the biotic disjunction between Amazonia and the Atlantic forest. We generated >5.8 kb sequence data from six markers for all seven nominal species of the subfamily as well as for newly discovered populations in order to (1) test the monophyly of Phyzelaphryninae, Adelophryne and Phyzelaphryne, (2) estimate species diversity within the subfamily, and (3) investigate their historical biogeography and diversification. Phylogenetic reconstruction confirmed the monophyly of each group and revealed deep subdivisions within Adelophryne and Phyzelaphryne, with three major clades in Adelophryne located in northern Amazonia, northern Atlantic forest and southern Atlantic forest. Our results suggest that the actual number of species in Phyzelaphryninae is, at least, twice the currently recognized species diversity, with almost every geographically isolated population representing an anciently divergent candidate species. Such results highlight the challenges for conservation, especially in the northern Atlantic forest where it is still degraded at a fast pace. Molecular dating revealed that Phyzelaphryninae originated in Amazonia and dispersed during early Miocene to the Atlantic forest. The two Atlantic forest clades of Adelophryne started to diversify some 7 Ma minimum, while the northern Amazonian Adelophryne diversified much earlier, some 13 Ma minimum. This striking biogeographic pattern coincides with major events that have shaped the face of the South American continent, as we know it today. (C) 2012 Elsevier Inc. All rights reserved.
Resumo:
Abstract Background The molecular phylogenetic relationships and population structure of the species of the Anopheles triannulatus complex: Anopheles triannulatus s.s., Anopheles halophylus and the putative species Anopheles triannulatus C were investigated. Methods The mitochondrial COI gene, the nuclear white gene and rDNA ITS2 of samples that include the known geographic distribution of these taxa were analyzed. Phylogenetic analyses were performed using Bayesian inference, Maximum parsimony and Maximum likelihood approaches. Results Each data set analyzed septely yielded a different topology but none provided evidence for the seption of An. halophylus and An. triannulatus C, consistent with the hypothesis that the two are undergoing incipient speciation. The phylogenetic analyses of the white gene found three main clades, whereas the statistical parsimony network detected only a single metapopulation of Anopheles triannulatus s.l. Seven COI lineages were detected by phylogenetic and network analysis. In contrast, the network, but not the phylogenetic analyses, strongly supported three ITS2 groups. Combined data analyses provided the best resolution of the trees, with two major clades, Amazonian (clade I) and trans-Andean + Amazon Delta (clade II). Clade I consists of multiple subclades: An. halophylus + An. triannulatus C; trans-Andean Venezuela; central Amazonia + central Bolivia; Atlantic coastal lowland; and Amazon delta. Clade II includes three subclades: Panama; cis-Andean Colombia; and cis-Venezuela. The Amazon delta specimens are in both clades, likely indicating local sympatry. Spatial and molecular variance analyses detected nine groups, corroborating some of subclades obtained in the combined data analysis. Conclusion Combination of the three molecular markers provided the best resolution for differentiation within An. triannulatus s.s. and An. halophylus and C. The latest two species seem to be very closely related and the analyses performed were not conclusive regarding species differentiation. Further studies including new molecular markers would be desirable to solve this species status question. Besides, results of the study indicate a trans-Andean origin for An. triannulatus s.l. The potential implications for malaria epidemiology remain to be investigated.
Resumo:
The pantropical family Eriocaulaceae includes ten genera and c. 1,400 species, with diversity concentrated in the New World. The last complete revision of the family was published more than 100 years ago, and until recently the generic and infrageneric relationships were poorly resolved. However, a multi-disciplinary approach over the last 30 years, using morphological and anatomical characters, has been supplemented with additional data from palynology, chemistry, embryology, population genetics, cytology and, more recently, molecular phylogenetic studies. This led to a reassessment of phylogenetic relationships within the family. In this paper we present new data for the ITS and trnL-F regions, analysed separately and in combination, using maximum parsimony and Bayesian inference. The data confirm previous results, and show that many characters traditionally used for differentiating and circumscribing the genera within the family are homoplasious. A new generic key with characters from various sources and reflecting the current taxonomic changes is presented.
Resumo:
A Bayesian nonparametric model for Taguchi's on-line quality monitoring procedure for attributes is introduced. The proposed model may accommodate the original single shift setting to the more realistic situation of gradual quality deterioration and allows the incorporation of an expert's opinion on the production process. Based on the number of inspections to be carried out until a defective item is found, the Bayesian operation for the distribution function that represents the increasing sequence of defective fractions during a cycle considering a mixture of Dirichlet processes as prior distribution is performed. Bayes estimates for relevant quantities are also obtained. (C) 2012 Elsevier B.V. All rights reserved.