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41.
Philip L. H. Yu K. F. Lam S. M. Lo 《Journal of the Royal Statistical Society. Series A, (Statistics in Society)》2005,168(3):583-597
Summary. Factor analysis is a powerful tool to identify the common characteristics among a set of variables that are measured on a continuous scale. In the context of factor analysis for non-continuous-type data, most applications are restricted to item response data only. We extend the factor model to accommodate ranked data. The Monte Carlo expectation–maximization algorithm is used for parameter estimation at which the E-step is implemented via the Gibbs sampler. An analysis based on both complete and incomplete ranked data (e.g. rank the top q out of k items) is considered. Estimation of the factor scores is also discussed. The method proposed is applied to analyse a set of incomplete ranked data that were obtained from a survey that was carried out in GuangZhou, a major city in mainland China, to investigate the factors affecting people's attitude towards choosing jobs. 相似文献
42.
A growing literature examines the empirical relationship between the joint reproductive preferences of marital partners and reproductive outcomes in Africa. Less explored is how spousal power in decision making may be influenced by lineage type. Using pooled data from Ghana, we investigate how lineage affects gendered reproductive decision outcomes and find some evidence that matrilineal women are more able than nonmatrilineal women to translate their reproductive preferences into action consistent with their goals. 相似文献
43.
Discrete time modelling of disease incidence time series by using Markov chain Monte Carlo methods 总被引:1,自引:0,他引:1
Alexander Morton Bärbel F. Finkenstädt 《Journal of the Royal Statistical Society. Series C, Applied statistics》2005,54(3):575-594
Summary. A stochastic discrete time version of the susceptible–infected–recovered model for infectious diseases is developed. Disease is transmitted within and between communities when infected and susceptible individuals interact. Markov chain Monte Carlo methods are used to make inference about these unobserved populations and the unknown parameters of interest. The algorithm is designed specifically for modelling time series of reported measles cases although it can be adapted for other infectious diseases with permanent immunity. The application to observed measles incidence series motivates extensions to incorporate age structure as well as spatial epidemic coupling between communities. 相似文献
44.
Point processes are the stochastic models most suitable for describing physical phenomena that appear at irregularly spaced
times, such as the earthquakes. These processes are uniquely characterized by their conditional intensity, that is, by the
probability that an event will occur in the infinitesimal interval (t, t+Δt), given the history of the process up tot. The seismic phenomenon displays different behaviours on different time and size scales; in particular, the occurrence of
destructive shocks over some centuries in a seismogenic region may be explained by the elastic rebound theory. This theory
has inspired the so-called stress release models: their conditional intensity translates the idea that an earthquake produces
a sudden decrease in the amount of strain accumulated gradually over time along a fault, and the subsequent event occurs when
the stress exceeds the strength of the medium. This study has a double objective: the formulation of these models in the Bayesian
framework, and the assignment to each event of a mark, that is its magnitude, modelled through a distribution that depends
at timet on the stress level accumulated up to that instant. The resulting parameter space is constrained and dependent on the data,
complicating Bayesian computation and analysis. We have resorted to Monte Carlo methods to solve these problems. 相似文献
45.
Christian P. Robert Xiao-Li Meng Jesper Møller Jeffrey S Rosenthal C Jennison M. A Hurn F Al-Awadhi Peter McCullagh Christophe Andrieu Arnaud Doucet Petros Dellaportas Ioulia Papageorgiou Ricardo S Ehlers Elena A Erosheva Stephen E Fienberg Jonathan J Forster Roger C Gill Nial Friel Peter Green David Hastie R King Hans R Künsch N. A. Lazar C Osinski 《Journal of the Royal Statistical Society. Series B, Statistical methodology》2003,65(1):39-55
46.
Cathy W. S. Chen F. C. Liu Mike K. P. So 《Australian & New Zealand Journal of Statistics》2008,50(1):29-51
To capture mean and variance asymmetries and time‐varying volatility in financial time series, we generalize the threshold stochastic volatility (THSV) model and incorporate a heavy‐tailed error distribution. Unlike existing stochastic volatility models, this model simultaneously accounts for uncertainty in the unobserved threshold value and in the time‐delay parameter. Self‐exciting and exogenous threshold variables are considered to investigate the impact of a number of market news variables on volatility changes. Adopting a Bayesian approach, we use Markov chain Monte Carlo methods to estimate all unknown parameters and latent variables. A simulation experiment demonstrates good estimation performance for reasonable sample sizes. In a study of two international financial market indices, we consider two variants of the generalized THSV model, with US market news as the threshold variable. Finally, we compare models using Bayesian forecasting in a value‐at‐risk (VaR) study. The results show that our proposed model can generate more accurate VaR forecasts than can standard models. 相似文献
47.
Michael S. Rendall Ryan Admiraal Alessandra DeRose Paola DiGiulio Mark S. Handcock Filomena Racioppi 《Statistical Methods and Applications》2008,17(4):519-539
In non-experimental research, data on the same population process may be collected simultaneously by more than one instrument.
For example, in the present application, two sample surveys and a population birth registration system all collect observations
on first births by age and year, while the two surveys additionally collect information on women’s education. To make maximum
use of the three data sources, the survey data are pooled and the population data introduced as constraints in a logistic
regression equation. Reductions in standard errors about the age and birth-cohort parameters of the regression equation in
the order of three-quarters are obtained by introducing the population data as constraints. A halving of the standard errors
about the education parameters is achieved by pooling observations from the larger survey dataset with those from the smaller
survey. The percentage reduction in the standard errors through imposing population constraints is independent of the total
survey sample size. 相似文献
48.
49.
Jerald F. Lawless 《Revue canadienne de statistique》2004,32(3):327-331
Oiler, Gomez & Calle (2004) give a constant sum condition for processes that generate interval‐censored lifetime data. They show that in models satisfying this condition, it is possible to estimate non‐parametrically the lifetime distribution based on a well‐known simplified likelihood. The author shows that this constant‐sum condition is equivalent to the existence of an observation process that is independent of lifetimes and which gives the same probability distribution for the observed data as the underlying true process. 相似文献
50.