Probabilistic wind power forecasts with an inverse power curve transformation and censored regression

Forecasting wind power is an important part of a successful integration of wind power into the power grid. Forecasts with lead times longer than 6 h are generally made by using statistical methods to post-process forecasts from numerical weather prediction systems. Two major problems that complicate this approach are the non-linear relationship between wind speed and power production and the limited range of power production between zero and nominal power of the turbine. In practice, these problems are often tackled by using non-linear non-parametric regression models. However, such an approach ignores valuable and readily available information: the power curve of the turbine's manufacturer. Much of the non-linearity can be directly accounted for by transforming the observed power production into wind speed via the inverse power curve so that simpler linear regression models can be used. Furthermore, the fact that the transformed power production has a limited range can be taken care of by employing censored regression models. In this study, we evaluate quantile forecasts from a range of methods: (i) using parametric and non-parametric models, (ii) with and without the proposed inverse power curve transformation and (iii) with and without censoring. The results show that with our inverse (power-to-wind) transformation, simpler linear regression models with censoring perform equally or better than non-linear models with or without the frequently used wind-to-power transformation.

Tests of sunspot number sequences: 3. Effects of regression procedures on the calibration of historic sunspot data

We use sunspot group observations from the Royal Greenwich Observatory (RGO) to investigate the effects of intercalibrating data from observers with different visual acuities. The tests are made by counting the number of groups RB above a variable cut-off threshold of observed total whole-spot area (uncorrected for foreshortening) to simulate what a lower acuity observer would have seen. The synthesised annual means of RB are then re-scaled to the full observed RGO group number RA using a variety of regression techniques. It is found that a very high correlation between RA and RB (rAB > 0.98) does not prevent large errors in the intercalibration (for example sunspot maximum values can be over 30 % too large even for such levels of rAB). In generating the backbone sunspot number (RBB), Svalgaard and Schatten (2015, this issue) force regression fits to pass through the scatter plot origin which generates unreliable fits (the residuals do not form a normal distribution) and causes sunspot cycle amplitudes to be exaggerated in the intercalibrated data. It is demonstrated that the use of Quantile-Quantile (“Q  Q”) plots to test for a normal distribution is a useful indicator of erroneous and misleading regression fits. Ordinary least squares linear fits, not forced to pass through the origin, are sometimes reliable (although the optimum method used is shown to be different when matching peak and average sunspot group numbers). However, other fits are only reliable if non-linear regression is used. From these results it is entirely possible that the inflation of solar cycle amplitudes in the backbone group sunspot number as one goes back in time, relative to related solar-terrestrial parameters, is entirely caused by the use of inappropriate and non-robust regression techniques to calibrate the sunspot data.

Systematic and random errors between collocated satellite ice water path observations

There remains large disagreement between ice-water path (IWP) in observational data sets, largely because the sensors observe different parts of the ice particle size distribution. A detailed comparison of retrieved IWP from satellite observations in the Tropics (!30 " latitude) in 2007 was made using collocated measurements. The radio detection and ranging(radar)/light detection and ranging (lidar) (DARDAR) IWP data set, based on combined radar/lidar measurements, is used as a reference because it provides arguably the best estimate of the total column IWP. For each data set, usable IWP dynamic ranges are inferred from this comparison. IWP retrievals based on solar reflectance measurements, in the moderate resolution imaging spectroradiometer (MODIS), advanced very high resolution radiometer–based Climate Monitoring Satellite Applications Facility (CMSAF), and Pathfinder Atmospheres-Extended (PATMOS-x) datasets, were found to be correlated with DARDAR over a large IWP range (~20–7000 g m -2 ). The random errors of the collocated data sets have a close to lognormal distribution, and the combined random error of MODIS and DARDAR is less than a factor of 2, which also sets the upper limit for MODIS alone. In the same way, the upper limit for the random error of all considered data sets is determined. Data sets based on passive microwave measurements, microwave surface and precipitation products system (MSPPS), microwave integrated retrieval system (MiRS), and collocated microwave only (CMO), are largely correlated with DARDAR for IWP values larger than approximately 700 g m -2 . The combined uncertainty between these data sets and DARDAR in this range is slightly less MODIS-DARDAR, but the systematic bias is nearly an order of magnitude.

Impact of socioeconomic and clinical factors on child oral health-related quality of life (COHRQoL)

Child oral health-related quality of life (COHRQoL) has been increasingly assessed; however, few studies appraised the influence of socioeconomic status on COHRQoL in developing countries. This study assessed the relationship of COHRQoL with socioeconomic backgrounds and clinical factors. This study followed a cross-sectional design, with a multistage random sample of 792 schoolchildren aged 12 years, representative of Santa Maria, a southern city in Brazil. Participants completed the Brazilian version of the Child Perceptions Questionnaire (CPQ(11-14)), their parents or guardians answered questions on socioeconomic status, and a dental examination provided information on the prevalence of caries, dental trauma and occlusion. The assessment of association used hierarchically adjusted Poisson regression models. Higher impacts on COHRQoL were observed for children presenting with untreated dental caries (RR 1.20; 95% CI 1.07-1.35) and maxillary overjet (RR 1.19; 95% CI 1.02-1.40). Socioeconomic factors also associated with COHRQoL; poorer scores were reported by children whose mothers have not completed primary education (RR 1.30; 95% CI 1.17-1.44) and those with lower household income (RR 1.13; 95% CI 1.02-1.26). Poor socioeconomic standings and poor dental status have a negative impact on COHRQoL; reducing health inequalities may demand dental programmes and policies targeting deprived population.

Dietary Quality and Associated Factors among Factory Workers in the Metropolitan Region of Sao Paulo, Brazil

The workplace is a manageable community-based setting for ensuring proper nutrition. This study aimed to evaluate dietary quality and associated factors among adult workers at a cosmetics factory in the metropolitan area of Sao Paulo, Brazil. This factory was actively participating in the Brazilian Workers` Meal Program, which was created to ensure workers` nutritional health. In this cross-sectional study, data on 202 adult workers were assessed using questionnaires (sociodemographic, anthropometric, and lifestyle characteristics) administered during August and September 2006. Dietary intake, measured by 24-hour dietary recall, was used to calculate the modified Healthy Eating Index (HEI). A repeated administration of the 24-hour dietary recall was applied in a random subsample to calculate the modified HEI adjusted for the within-person variation in intake. Mean adjusted modified HEI scores were analyzed using multiple linear regression adjusted for energy. The mean adjusted modified HEI score was 72.3 +/- 8.0. The lowest adjusted modified HEI components scores were ""milk and dairy products"" (4.4 +/- 3.2) and ""sodium"" (3.7 +/- 3.1). Two percent of workers had ""poor diet"" (adjusted modified HEI score <51 points) and the majority (87%) had ""diet that needs modification"" (adjusted modified HEI score between 51 and 80), despite their participation in the meal program. Adjusted modified HEI scores were considerably higher for men (74.7 +/- 7.0) than for women (66.9 +/- 8.2) and for normal body mass index (calculated as kg/m(2)) (73.3 +/- 7.8) than for overweight/obese (70.9 +/- 8.1). Based on these results, the vast majority of workers were found to have diets that needed improvement. Individuals with higher-quality diets were more likely to have lower body mass index and to be male. J Am Diet Assoc. 2010;110:786-790.

Self-rated oral health and associated factors in Brazilian elders

Objective: Self-rating provides a simple direct way of capturing perceptions of health. The objective of this study was to estimate the prevalence and associated factors of poor self-rated oral health among elders. Methods: National data from a cross-sectional population-based study with a multistage random sample of 4786 Brazilian older adults (aged 65-74) in 250 towns were analysed. Data collection included oral examinations (WHO 1997) and struct-ured interviews at elderly households. The outcome was measured by a single five-point-response-scale question dichotomized into `poor` (fair/poor/very poor) and `good` (good/very good) self-rated oral health. Data analyses used Poisson regression models stratified by sex. Results: The prevalence of poor self-rated oral health was 46.6% (95% CI: 45.2-48%) in the whole sample, 50.3% (48-52.5) in men and 44.2% (42.4-46) in women. Higher prevalence ratios (PR) were found in elders reporting unfavourable dental appearance (PR = 2.31; 95% CI: 2.02-2.65), poor chewing ability (PR = 1.64; CI: 1.48-1.8) and dental pain (PR = 1.44; CI: 1.04-1.23) in adjusted analysis. Poor self-perception was also associated with being men, black, unfavourable socioeconomic circumstances, unfavourable clinical oral health and with not using or needing a dental prosthesis. Conclusion: Assessment and understanding of self-rated oral health should take into account social factors, subjective and clinical oral symptoms.

A Longitudinal Three-Center Study of Dental Arch Relationship in Patients With Bilateral Cleft Lip and Palate

Objective: To compare and evaluate longitudinally the dental arch relationships from 4.5 to 13.5 years of age with the Bauru-BCLP Yardstick in a large sample of patients with bilateral cleft lip and palate (BCLP). Design: Retrospective longitudinal intercenter outcome study. Patients: Dental casts of 204 consecutive patients with complete BCLP were evaluated at 6, 9, and 12 years of age. All models were identified only by random identification numbers. Setting: Three cleft palate centers with different treatment protocols. Main Outcome Measures: Dental arch relationships were categorized with the Bauru-BCLP yardstick. Increments for each interval (from 6 to 9 years, 6 to 12 years, and 9 to 12 years) were analyzed by logistic and linear regression models. Results: There were no significant differences in outcome measures between the centers at age 12 or at age 9. At age 6, center B showed significantly better results (p = .027), but this difference diminished as the yardstick score for this group increased over time (linear regression analysis), the difference with the reference category (center C, boys) for the intervals 6 to 12 and 9 to 12 years being 10.4% (p = .041) and 12.9% (p = .009), respectively. Conclusions: Despite different treatment protocols, dental arch relationships in the three centers were comparable in final scores at age 9 and 12 years. Delaying hard palate closure and employing infant orthopedics did not appear to be advantageous in the long run. Premaxillary osteotomy employed in center B appeared to be associated with less favorable development of the dental arch relationship between 9 and 12 years.

Random primordial magnetic fields and the gas content of dark matter haloes

We recently predicted the existence of random primordial magnetic fields (RPMFs) in the form of randomly oriented cells with dipole-like structure with a cell size L(0) and an average magnetic field B(0). Here, we investigate models for primordial magnetic field with a similar web-like structure, and other geometries, differing perhaps in L(0) and B(0). The effect of RPMF on the formation of the first galaxies is investigated. The filtering mass, M(F), is the halo mass below which baryon accretion is severely depressed. We show that these RPMF could influence the formation of galaxies by altering the filtering mass and the baryon gas fraction of a halo, f(g). The effect is particularly strong in small galaxies. We find, for example, for a comoving B(0) = 0.1 mu G, and a reionization epoch that starts at z(s) = 11 and ends at z(e) = 8, for L(0) = 100 pc at z = 12, the f(g) becomes severely depressed for M < 10(7) M(circle dot), whereas for B(0) = 0 the f(g) becomes severely depressed only for much smaller masses, M < 10(5) M(circle dot). We suggest that the observation of M(F) and f(g) at high redshifts can give information on the intensity and structure of primordial magnetic fields.

Non-random reef use by fishes at two dominant zones in a tropical, algal-dominated coastal reef

Habitat use and the processes which determine fish distribution were evaluated at the reef flat and reef crest zones of a tropical, algal-dominated reef. Our comparisons indicated significant differences in the majority of the evaluated environmental characteristics between zones. Also, significant differences in the abundances of twelve, from thirteen analyzed species, were observed within and between-sites. According to null models, non-random patterns of species co-occurrences were significant, suggesting that fish guilds in both zones were non-randomly structured. Unexpectedly, structural complexity negatively affected overall species richness, but had a major positive influence on highly site-attached species such as a damselfish. Depth and substrate composition, particularly macroalgae cover, were positive determinants for the fish assemblage structure in the studied reef, prevailing over factors such as structural complexity and live coral cover. Our results are conflicting with other studies carried out in coral-dominated reefs of the Caribbean and Pacific, therefore supporting the idea that the factors which may potentially influence reef fish composition are highly site-dependent and variable.

The Prospective and Retrospective Memory Questionnaire: A population-based random sampling study

The Prospective and Retrospective Memory Questionnaire (PRMQ) has been shown to have acceptable reliability and factorial, predictive, and concurrent validity. However, the PRMQ has never been administered to a probability sample survey representative of all ages in adulthood, nor have previous studies controlled for factors that are known to influence metamemory, such as affective status. Here, the PRMQ was applied in a survey adopting a probabilistic three-stage cluster sample representative of the population of Sao Paulo, Brazil, according to gender, age (20-80 years), and economic status (n=1042). After excluding participants who had conditions that impair memory (depression, anxiety, used psychotropics, and/or had neurological/psychiatric disorders), in the remaining 664 individuals we (a) used confirmatory factor analyses to test competing models of the latent structure of the PRMQ, and (b) studied effects of gender, age, schooling, and economic status on prospective and retrospective memory complaints. The model with the best fit confirmed the same tripartite structure (general memory factor and two orthogonal prospective and retrospective memory factors) previously reported. Women complained more of general memory slips, especially those in the first 5 years after menopause, and there were more complaints of prospective than retrospective memory, except in participants with lower family income.

Heteroscedastic Nonlinear Regression Models

In this article, we present a generalization of the Bayesian methodology introduced by Cepeda and Gamerman (2001) for modeling variance heterogeneity in normal regression models where we have orthogonality between mean and variance parameters to the general case considering both linear and highly nonlinear regression models. Under the Bayesian paradigm, we use MCMC methods to simulate samples for the joint posterior distribution. We illustrate this algorithm considering a simulated data set and also considering a real data set related to school attendance rate for children in Colombia. Finally, we present some extensions of the proposed MCMC algorithm.

Regression Models with Heteroscedasticity using Bayesian Approach

In this paper, we compare the performance of two statistical approaches for the analysis of data obtained from the social research area. In the first approach, we use normal models with joint regression modelling for the mean and for the variance heterogeneity. In the second approach, we use hierarchical models. In the first case, individual and social variables are included in the regression modelling for the mean and for the variance, as explanatory variables, while in the second case, the variance at level 1 of the hierarchical model depends on the individuals (age of the individuals), and in the level 2 of the hierarchical model, the variance is assumed to change according to socioeconomic stratum. Applying these methodologies, we analyze a Colombian tallness data set to find differences that can be explained by socioeconomic conditions. We also present some theoretical and empirical results concerning the two models. From this comparative study, we conclude that it is better to jointly modelling the mean and variance heterogeneity in all cases. We also observe that the convergence of the Gibbs sampling chain used in the Markov Chain Monte Carlo method for the jointly modeling the mean and variance heterogeneity is quickly achieved.

Methods of Estimation in Multiple Linear Regression: Application to Clinical Data

Nesse artigo, tem-se o interesse em avaliar diferentes estratégias de estimação de parâmetros para um modelo de regressão linear múltipla. Para a estimação dos parâmetros do modelo foram utilizados dados de um ensaio clínico em que o interesse foi verificar se o ensaio mecânico da propriedade de força máxima (EM-FM) está associada com a massa femoral, com o diâmetro femoral e com o grupo experimental de ratas ovariectomizadas da raça Rattus norvegicus albinus, variedade Wistar. Para a estimação dos parâmetros do modelo serão comparadas três metodologias: a metodologia clássica, baseada no método dos mínimos quadrados; a metodologia Bayesiana, baseada no teorema de Bayes; e o método Bootstrap, baseado em processos de reamostragem.

Bayesian nonlinear regression models with scale mixtures of skew-normal distributions: Estimation and case influence diagnostics

The purpose of this paper is to develop a Bayesian analysis for nonlinear regression models under scale mixtures of skew-normal distributions. This novel class of models provides a useful generalization of the symmetrical nonlinear regression models since the error distributions cover both skewness and heavy-tailed distributions such as the skew-t, skew-slash and the skew-contaminated normal distributions. The main advantage of these class of distributions is that they have a nice hierarchical representation that allows the implementation of Markov chain Monte Carlo (MCMC) methods to simulate samples from the joint posterior distribution. In order to examine the robust aspects of this flexible class, against outlying and influential observations, we present a Bayesian case deletion influence diagnostics based on the Kullback-Leibler divergence. Further, some discussions on the model selection criteria are given. The newly developed procedures are illustrated considering two simulations study, and a real data previously analyzed under normal and skew-normal nonlinear regression models. (C) 2010 Elsevier B.V. All rights reserved.