Semiparametric Regression and Mortality Rate Prediction

This dissertation is divided into two parts. In the first part we consider the general multivariate multiple sample semiparametric density ratio model. In this model one distribution serves as a reference or baseline, and all other distributions are weighted tilts of the reference. The weights are considered known up to a parameter. All the parameters in the model, as well as the reference distribution, are estimated from the combined data from all samples. A kernel-based density estimator can be constructed based on the semiparametric model. In this dissertation we discuss the asymptotic theory and convergence properties for the semiparametric kernel density estimator. The estimator is shown to be not only consistent, but also more efficient than the general kernel density estimator. Several ways for selecting the bandwidth are also discussed. This opens the door to regression analysis with random covariates from a semiparametric perspective where information is combined from multiple multivariate sources. Accordingly, each multivariate distribution and a corresponding conditional expectation (or regression) of interest is then estimated from the combined data from all sources. Graphical and quantitative diagnostic tools are suggested to assess model validity. The method is applied to real and simulated data. Comparisons are made with multiple regression, generalized additive models (GAM) and nonparametric kernel regression. In the second part we study mortality rate prediction. The National Center for Health Statistics (NCHS) uses observed mortality data to publish race-gender specific life tables for individual states decennially. At ages over 85 years, the reliability of death rates based on these data is compromised to some extent by age misreporting. The eight-parameter Heligman-Pollard parametric model is then used to smooth the data and obtain estimates/extrapolation of mortality rates for advanced ages. In States with small sub-populations the observed mortality rates are often zero, particularly among young ages. The presence of zero death rates makes the fitting of the Heligman-Pollard model difficult and at times outright impossible. In addition, since death rates are reported on a log scale, zero mortality rates are problematic. To overcome observed zero death rates, appropriate probability models are used. Using these models, observed zero mortality rates are replaced by the corresponding expected values. This enables using logarithmic transformations, and the fitting of the Heligman-Pollard model to produce mortality estimates for ages 0 - 130 years

Voice activity detection based on density ratio estimation and system combination

Abstract-We propose a robust voice activity detection (VAD) based on density ratio estimation. In highly noisy environments, the likelihood ratio test (LRT) is effective. Conventional LRT estimates both speech and noise models, calculates the likelihood of each model, and uses ratios of such likelihood to detect speech. However, in LRT, the likelihood ratio of speech and noise models is required, whereas likelihood of individual models is not necessarily required. The framework of the density ratio estimation models likelihood ratio functions by a kernel and directly generates a likelihood ratio. Applying density ratio estimation to VAD requires that feature selection and noise adaptation must be considered. This is because the density ratio estimation constrains the shape of the likelihood ratio functions and speech is dynamic. This paper addresses these problems. To improve accuracy, the proposed method is combined with conventional LRT. Experimental results using CENSREC-1-C show that the proposed method is more effective than conventional methods, especially in non-stationary noisy environments

ISBIS 2016: Meeting on Statistics in Business and Industry

This Book includes the abstracts of the talks presented at the 2016 International Symposium on Business and Industrial Statistics, held at Barcelona, June 8-10, 2016, hosted at the Universitat Politècnica de Catalunya - Barcelona TECH, by the Department of Statistics and Operations Research. The location of the meeting was at ETSEIB Building (Escola Tecnica Superior d'Enginyeria Industrial) at Avda Diagonal 647. The meeting organizers celebrated the continued success of ISBIS and ENBIS society, and the meeting draw together the international community of statisticians, both academics and industry professionals, who share the goal of making statistics the foundation for decision making in business and related applications. The Scientific Program Committee was constituted by: David Banks, Duke University Amílcar Oliveira, DCeT - Universidade Aberta and CEAUL Teresa A. Oliveira, DCeT - Universidade Aberta and CEAUL Nalini Ravishankar, University of Connecticut Xavier Tort Martorell, Universitat Politécnica de Catalunya, Barcelona TECH Martina Vandebroek, KU Leuven Vincenzo Esposito Vinzi, ESSEC Business Schoo

Growth Econometrics

This paper provides a survey and synthesis of econometric tools that have been employed to study economic growth. While these tools range across a variety of statistical methods, they are united in the common goals of first, identifying interesting contemporaneous patterns in growth data and second, drawing inferences on long-run economic outcomes from cross-section and temporal variation in growth. We describe the main stylized facts that have motivated the development of growth econometrics, the major statistical tools that have been employed to provide structural explanations for these facts, and the primary statistical issues that arise in the study of growth data. An important aspect of the survey is attention to the limits that exist in drawing conclusions from growth data, limits that reflect model uncertainty and the general weakness of available data relative to the sorts of questions for which they are employed.

Prevalent Herpes Simplex Virus-2 Increases the Risk of Incident Bacterial Vaginosis in Women from South Africa.

Studies have shown that women diagnosed with herpes simplex virus-2 (HSV-2) have a higher risk for bacterial vaginosis (BV) infection. We investigated the presence of HSV-2 infections as a risk factor for incident BV infections in high risk, Human immunodeficiency virus (HIV) uninfected women enrolled in a HIV prevention trial in Durban, South Africa. The Vaginal and Oral Interventions to Control the Epidemic trial was a multicentre, double blinded, randomized controlled trial which was designed to estimate the effectiveness of daily treatment with vaginal tenofovir gel, oral tenofovir disoproxil fumarate and oral Truvada in preventing HIV-1 infection in women. Women provided samples for the diagnosis of HSV-2 and BV. The presence of HSV-2 antibodies was detected using HerpeSelect™ ELISA IgG. Bacterial vaginosis was diagnosed using the Nugent scoring system. To assess the risk of BV incidence, modelled as a time-dependent variable, we used the Andersen-Gill model with robust variance estimation and Efron methods for ties. Overall, 2750 women were enrolled in the VOICE trial at our study sites. Women who had a HSV-2 infection at enrolment were shown to be at increased risk for incident BV infections (adjusted hazard ratio 1.17, 95% CI 1.08, 1.27, p ≤ 0.001). In addition, being of a young age, being unmarried and having a partner that has other partners were significantly associated with subsequent BV infection. Our findings therefore advocate the need for strengthening STI prevention efforts among women in high burden STI settings

Unionism and peer-referencing

This study assesses the “fair-wage-effort” hypothesis, by examining (a) the relationship between relative wage comparisons and job satisfaction and quitting intensions, and (b) the relative ranking of stated effort inducing-incentives, in a novel dataset of unionised and non-unionised European employees. By distinguishing between downward and upward-looking wage comparisons, it is shown that wage comparisons to similar workers exert an asymmetric impact on the job satisfaction of union workers, a pattern consistent with inequity-aversion and conformism to the reference point. Moreover, union workers evaluate peer observation and good industrial relations more highly than payment and other incentives. In contrast, non-union workers are found to be more status-seeking in their satisfaction responses and less dependent on their peers in their effort choices The results are robust to endogenous union membership, considerations of generic loss aversion and across different tenure profiles. They are supportive of the individual egalitarian bias of collective wage determination and self-enforcing effort norms.EPICURUS, a project supported by the European Commission through the 5th Framework Programme “Improving Human Potential” (contract number: HPSE-CT-2002-00143