Statistical modelling of counts with a simple integer-valued bilinear process

The aim of this work is the statistical modelling of counts assuming low values and exhibiting sudden and large bursts that occur randomly in time. It is well known that bilinear processes capture these kind of phenomena. In this work the integer-valued bilinear INBL(1,0,1,1) model is discussed and some properties are reviewed. Classical and Bayesian methodologies are considered and compared through simulation studies, namely to obtain estimates of model parameters and to calculate point and interval predictions. Finally, an empirical application to real epidemiological count data is also presented to attest for its practical applicability in data analysis.publishe

High-latitude Southern Hemisphere fire history during the mid to late Holocene (6000–750 BP)

We determined the specific biomass burning biomarker levoglucosan in an ice core from the TALos Dome Ice CorE drilling project (TALDICE) during the mid- to late Holocene (6000–750 BP). The levoglucosan record is characterized by a long-term increase with higher rates starting at 4000 BP and peaks between 2500 and 1500 BP. The anomalous increase in levoglucosan centered at 2000 BP is consistent with other Antarctic biomass burning records. Multiple atmospheric phenomena affect the coastal Antarctic Talos Dome drilling site, where the Southern Annular Mode (SAM) is the most prominent as the Southern Annular Mode Index (SAMA) correlates with stable isotopes in precipitation throughout the most recent 1000 years of the ice core. If this connection remains throughout the mid- to late Holocene, then our results demonstrate that changes in biomass burning, rather than changes in atmospheric transport, are the major influence on the TALDICE levoglucosan record. Comparisons with charcoal syntheses help evaluate fire sources, showing a greater contribution from southern South American fires than from Australian biomass burning. The levoglucosan peak centered at 2000 BP occurs during a cool period throughout the Southern Hemisphere, yet during a time of increased fire activity in both northern and southern Patagonia. This peak in biomass burning is influenced by increased vegetation in southern South America from a preceding humid period, in which the vegetation desiccated during the following cool, dry period. The Talos Dome ice core record from 6000 to 750 BP currently does not provide clear evidence that the fire record may be strongly affected by anthropogenic activities during the mid- to late Holocene, although we cannot exclude at least a partial influence

Likelihood Estimation for the INAR(p) Model by Saddlepoint Approximation

Saddlepoint techniques have been used successfully in many applications, owing to the high accuracy with which they can approximate intractable densities and tail probabilities. This article concerns their use for the estimation of high-order integer-valued autoregressive, INAR(p), processes. Conditional least squares estimation and maximum likelihood estimation have been proposed for INAR(p) models, but the first is inefficient for estimating parametric models, and the second becomes difficult to implement as the order p increases. We propose a simple saddlepoint approximation to the log-likelihood that performs well even in the tails of the distribution and with complicated INAR models. We consider Poisson and negative binomial innovations, and show empirically that the estimator that maximises the saddlepoint approximation behaves very similarly to the maximum likelihood estimator in realistic settings. The approach is applied to data on meningococcal disease counts. Supplementary materials for this article are available online

Two Cholesky-log-GARCH models for multivariate volatilities

Parsimonious estimation of high-dimensional covariance matrices is of fundamental importance in multivariate statistics. Typical examples occur in finance, where the instantaneous dependence among several asset returns should be taken into account. Multivariate GARCH processes have been established as a standard approach for modelling such data. However, the majority of GARCH-type models are either based on strong assumptions that may not be realistic or require restrictions that are often too hard to be satisfied in practice. We consider two alternative decompositions of time-varying covariance matrices Σt. The first is based on the modified Cholesky decomposition of the covariance matrices and second relies on the hyperspherical parametrization of the standard Cholesky factor of their correlation matrices Rt. Then, we combine each Cholesky factor with the log-GARCH models for the corresponding time–varying volatilities and use a quasi maximum likelihood approach to estimate the parameters. Using log-GARCH models is quite natural for achieving the positive definiteness of Σt and this is a novelty of this work. Application of the proposed methodologies to two real financial datasets reveals their usefulness in terms of parsimony, ease of implementation and stresses the choice of the appropriate models using familiar data-driven processes such as various forms of the exploratory data analysis and regression

Risk assessment of diesel exhaust and lung cancer: Combining human and animal studies after adjustment for biases in epidemiological studies

Background: Risk assessment requires dose-response data for the evaluation of the relationship between exposure to an environmental stressor and the probability of developing an adverse health effect. Information from human studies is usually limited and additional results from animal studies are often needed for the assessment of risks in humans. Combination of risk estimates requires an assessment and correction of the important biases in the two types of studies. In this paper we aim to illustrate a quantitative approach to combining data from human and animal studies after adjusting for bias in human studies. For our purpose we use the example of the association between exposure to diesel exhaust and occurrence of lung cancer. Methods. Firstly, we identify and adjust for the main sources of systematic error in selected human studies of the association between occupational exposure to diesel exhaust and occurrence of lung cancer. Evidence from selected animal studies is also accounted for by extrapolating to average ambient, occupational exposure concentrations of diesel exhaust. In a second stage, the bias adjusted effect estimates are combined in a common effect measure through meta-analysis. Results: The random-effects pooled estimate (RR) for exposure to diesel exhaust vs. non-exposure was found 1.37 (95% C.I.: 1.08-1.65) in animal studies and 1.59 (95% C.I.: 1.09-2.10) in human studies, whilst the overall was found equal to 1.49 (95% C.I.: 1.21-1.78) with a greater contribution from human studies. Without bias adjustment in human studies, the pooled effect estimate was 1.59 (95% C.I.: 1.28-1.89). Conclusions: Adjustment for the main sources of uncertainty produced lower risk estimates showing that ignoring bias leads to risk estimates potentially biased upwards. © 2011 Pedeli et al; licensee BioMed Central Ltd

Medical students' perceptions on factors influencing a surgical career: The fate of general surgery in Greece

Background: A decline of medical students' interest in a general surgery career is occurring in the Western medical world. We sought data on the mentality of Greek students toward specialty selection, and we determined whether trends indicated a decline in interest for general surgery in Greece. Methods: A structured questionnaire was distributed to 3 groups of medical students: to pre-4th-year (group 1) surgical clerkship, post-4th-year (group 2) surgical clerkship, and post-6th-year internship students in surgery (group 3). The questions covered a wide spectrum of data including career choices, influential factors, and satisfaction rates on educational and training issues. Results: From a total of 500 distributed questionnaires 363 were returned. Most students (63.1%) indicated preference toward nonsurgical (medical) specialties. Surgical specialties within the 3 groups gathered 19.5% (group 1), 26.5% (group 2) and 31.2% (group 3) preference rates. Among surgical specialties, general surgery was chosen by 29.4% in group 1, 10.0% in group 2, and 17.9% in group 3. The most common criterion for specialty selection was "quality of life" (68.6%) among group 1 students and "patient contact" for group 2 and group 3 students (77.3% and 65.3%, respectively). Among the 96 students who chose surgical specialties, the most common criterion for specialty selection was "scientific challenge" (100%) in group 1 and "patient contact" in groups 2 and 3 (62.5% and 69.2%, respectively). The 3 more frequently chosen factors that influenced the "picture" of surgery positively were attending live surgery cases in the operating room (37.6%), clinical experience (29.6%), and patient care (14.4%), followed by assisting in the operating room (8.8%). Conclusion: Our survey suggests a limited interest of Greek medical students for surgical specialties and general surgery in particular. As the medical curriculum is restructured, our data underscore the need for actions by surgical educators and medical school authorities so as to enhance the interest of medical students in general surgery in Greece. © 2010 Mosby, Inc. All rights reserved

Interobserver variability, and visual and quantitative parameters of 123I-FP-CIT SPECT (DaTSCAN) studies

Objective To evaluate the degree of interobserver agreement in the visual interpretation of 123I-FP-CIT studies and to investigate for potential associations between visual and semi-quantitative parameters. Methods Eighty-nine 123I-FP-CIT studies were blindly reviewed by 3 independent observers: a consultant, a resident doctor and a radiographer. They classified every study as either "normal" or "abnormal" and assigned visual 123I-FP-CIT uptake scores (2: normal, 1: reduced and 0: no uptake) in basal ganglia nuclei (right and left putamina and caudate nuclei) on every scan. Striatal 123I-FP-CIT binding ratios were calculated using crescent- ROI software. The interobserver agreement for the interpretation of studies and for visual score assignment was evaluated by means of κ statistics. We investigated for associations of binding ratios with visual scores and clinical parameters; patients' clinical diagnoses served as the reference standard. Results There was excellent interobserver agreement (j 0.89-0.93) in classifying studies as "normal" or "abnormal" and fine agreement in assignment of visual scores (j 0.71-0.80 for putamina and 0.50-0.79 for caudate nuclei). Nuclei with scores of 1 and 0 showed significantly reduced binding ratios (about 30 and 50%, respectively) compared with the nuclei scored as 2. ROC analysis indicated the optimal cutoff point of striatal binding ratio at 3.8 (sensitivity 98.5%, specificity 95%) for the detection of parkinsonian syndromes. Striatal binding ratios were negatively associated with age in normal subjects and disease duration in Parkinson's disease patients. Conclusion Visual interpretation of 123I-FP-CIT studies showed very good interobserver agreement. We found significant associations among visual, semi-quantitative and clinical parameters. © The Japanese Society of Nuclear Medicine 2012