[PDF] Top 20 Bayesian analysis of circular data using wrapped distributions

... continuous wrapped densities on the circle using MCMC ...that using this method, we can easily obtain samples from the joint posterior distribution, and hence, compute the posterior summary values ... See full document

... fitting wrapped distributions was given by Fisher and Lee (1994) who used the Expectation Maximization (EM) algorithm techniques to obtain parameter estimates from the Wrapped Normal ...the ... See full document

... of circular distributions, obtained by wrapping discrete skew Laplace distribution on Z = 0, ±1, ±2, around a unit ...many wrapped distributions, here closed form expressions exist for the ... See full document

... that using improper prior distributions for the parameter k could not guarantee that the posterior distribution was proper, as this depended on the data set (as was observed in our application with ... See full document

... with wrapped Cauchy error to the functional case when both variables are subjected to wrapped Cauchy ...the analysis of wind directions data at two cities in the Gaza strip, ... See full document

... two data sets, from eastern Bangladesh, are presented by Davis and Sampson ...the data in the pre- vious section these data are orientations without a preferred ...orientation data can be ... See full document

... particular, Bayesian analyses for complicated models can be carried out on a fixed data set relatively simple using Monte Carlo methods to simulate posterior ...to data more effectively and ... See full document

... In experiments with life testing, it has been found that the lifetime may often be reasonably described by an exponential distribution. The exponential distribu- tion has been used as a model, at least as a rst ... See full document

...     Samples of size n = 30, 60 and 100 were generated from the two component mixture of the shifted Gompertz distribution. A well-known procedure in simulation for computer generation of random variables is the ... See full document

... for Bayesian analysis of an ordered response model, but it converges slowly, especially with a large ...latent data and cutpoints jointly, which requires an M–H ... See full document

... the Bayesian methodologies for analyzing experimental ...prior distributions of the parameters. Bayesian methods are well established in general linear models, where the design matrix is of full ... See full document

... the Bayesian inference and prediction of the inverse Weibull distribution for type-II censored ...the Bayesian analysis of the mixture of Power function distribution using the complete and the ... See full document

... is significant and positive for all three fitted models providing evidence of right-skewness for our data. And DF parameter in ST and SS model is significant and confirms its sufficient disparity from the normal ... See full document

... survival analysis has experienced tremendous growth during the latter half of the 20th ...Survival analysis is a statistical method for data analysis where the outcome variable of interest is ... See full document

... Agin and Godbole [1] proposed a nonparametric test for randomness based on the number of success runs of length k in a linear sequence of n Bernoulli trials, for an alternative hypothesis of clustering. Furthermore, ... See full document

... isoscapes, data coverage in some regions of hydrological interest ...isotope data, we generated rainfall isoscapes for Namibia (dryland) using the cokriging method and compared it to a globally ... See full document

... nuclear data libraries so that simulations performed with them are in good agreement with experimental integral ...nuclear data fi les uncertainties towards the integral observables produces k eff ... See full document

... as circular, rectangular, diamond, triangular, trapezoidal and even irregular ...However, circular and rectangular openings are the most common ones in ...are circular, square or nearly square in ... See full document

... (d) Multiple displays cater for differences in people’s preferences as well as allowing for different statistical needs. The dot plots and histogram give good visual representations of the data sets and are best ... See full document

... to be important covariates when describing the size and shape of the face landmark configurations, and so we develop some Bayesian regression models to explore the relationship. A set of 3D facial images was ... See full document