Robust Estimates of the Negative Binomial Model

We consider robust parametric procedures for univariate discrete distributions, focusing on the negative binomial model. The procedures are based on three steps: ?First, a very robust, but possibly inefficient, estimate of the model parameters is computed. ?Second, this initial model is used to identify outliers, which are then removed from the sample. ?Third, a corrected maximum likelihood estimator is computed with the remaining observations. The final estimate inherits the breakdown point (bdp) of the initial one and its efficiency can be significantly higher. Analogous procedures were proposed in [1], [2], [5] for the continuous case. A comparison of the asymptotic bias of various estimates under point contamination points out the minimum Neyman's chi-squared disparity estimate as a good choice for the initial step. Various minimum disparity estimators were explored by Lindsay [4], who showed that the minimum Neyman's chi-squared estimate has a 50% bdp under point contamination; in addition, it is asymptotically fully efficient at the model. However, the finite sample efficiency of this estimate under the uncontaminated negative binomial model is usually much lower than 100% and the bias can be strong. We show that its performance can then be greatly improved using the three step procedure outlined above. In addition, we compare the final estimate with the procedure described in

Horizontal Grid Size Selection and its Influence on Mesoscale Model Simulations

The use of two-dimensional spectral analysis applied to terrain heights in order to determine characteristic terrain spatial scales and its subsequent use for the objective definition of an adequate grid size required to resolve terrain forcing are presented in this paper. In order to illustrate the influence of grid size, atmospheric flow in a complex terrain area of the Spanish east coast is simulated by the Regional Atmospheric Modeling System (RAMS) mesoscale numerical model using different horizontal grid resolutions. In this area, a grid size of 2 km is required to account for 95% of terrain variance. Comparison among results of the different simulations shows that, although the main wind behavior does not change dramatically, some small-scale features appear when using a resolution of 2 km or finer. Horizontal flow pattern differences are significant both in the nighttime, when terrain forcing is more relevant, and in the daytime, when thermal forcing is dominant. Vertical structures also are investigated, and results show that vertical advection is influenced highly by the horizontal grid size during the daytime period. The turbulent kinetic energy and potential temperature vertical cross sections show substantial differences in the structure of the planetary boundary layer for each model configuration

Stratification of regional sampling by model-predicted changes of carbon stocks in Forested mineral soils

Selective papers of the workshop on "Development of models and forest soil surveys for monitoring of soil carbon", Koli, Finland, April 5-9 2006.

Hydrological simulation using SWAT model in headwater basin in Southeast Brazil

Hydrological models are important tools that have been used in water resource planning and management. Thus, the aim of this work was to calibrate and validate in a daily time scale, the SWAT model (Soil and Water Assessment Tool) to the watershed of the Galo creek , located in Espírito Santo State. To conduct the study we used georeferenced maps of relief, soil type and use, in addition to historical daily time series of basin climate and flow. In modeling were used time series corresponding to the periods Jan 1, 1995 to Dec 31, 2000 and Jan 1, 2001 to Dec 20, 2003 for calibration and validation, respectively. Model performance evaluation was done using the Nash-Sutcliffe coefficient (E NS) and the percentage of bias (P BIAS). SWAT evaluation was also done in the simulation of the following hydrological variables: maximum and minimum annual daily flowsand minimum reference flows, Q90 and Q95, based on mean absolute error. E NS and P BIAS were, respectively, 0.65 and 7.2% and 0.70 and 14.1%, for calibration and validation, indicating a satisfactory performance for the model. SWAT adequately simulated minimum annual daily flow and the reference flows, Q90 and Q95; it was not suitable in the simulation of maximum annual daily flows.

Bartlett-Lewis of rectangular pulse modified model: estimate of parameters for simulation of precipitation in sub-hourly duration

The Bartlett-Lewis Rectangular Pulse Modified (BLPRM) model simulates the precipitous slide in the hourly and sub-hourly and has six parameters for each of the twelve months of the year. This study aimed to evaluate the behavior of precipitation series in the duration of 15 min, obtained by simulation using the model BLPRM in situations: (a) where the parameters are estimated from a combination of statistics, creating five different sets; (b) suitability of the model to generate rain. To adjust the parameters were used rain gauge records of Pelotas/RS/Brazil, which statistics were estimated - mean, variance, covariance, autocorrelation coefficient of lag 1, the proportion of dry days in the period considered. The results showed that the parameters related to the time of onset of precipitation (λ) and intensities (μx) were the most stable and the most unstable were ν parameter, related to rain duration. The BLPRM model adequately represented the mean, variance, and proportion of the dry period of the series of precipitation lasting 15 min and, the time dependence of the heights of rain, represented autocorrelation coefficient of the first retardation was statistically less simulated series suitability for the duration of 15 min.

Climate trends in the municipality of Pelotas, state of Rio Grande do Sul, Brazil

ABSTRACTChanges in the frequency of occurrence of extreme weather events have been pointed out as a likely impact of global warming. In this context, this study aimed to detect climate change in series of extreme minimum and maximum air temperature of Pelotas, State of Rio Grande do Sul, (1896 - 2011) and its influence on the probability of occurrence of these variables. We used the general extreme value distribution (GEV) in its stationary and non-stationary forms. In the latter case, GEV parameters are variable over time. On the basis of goodness-of-fit tests and of the maximum likelihood method, the GEV model in which the location parameter increases over time presents the best fit of the daily minimum air temperature series. Such result describes a significant increase in the mean values of this variable, which indicates a potential reduction in the frequency of frosts. The daily maximum air temperature series is also described by a non-stationary model, whose location parameter decreases over time, and the scale parameter related to sample variance rises between the beginning and end of the series. This result indicates a drop in the mean of daily maximum air temperature values and increased dispersion of the sample data.

Statistical segmentation methods and color variance analysis of retinal images

In this research, the effectiveness of Naive Bayes and Gaussian Mixture Models classifiers on segmenting exudates in retinal images is studied and the results are evaluated with metrics commonly used in medical imaging. Also, a color variation analysis of retinal images is carried out to find how effectively can retinal images be segmented using only the color information of the pixels.

The terrestrial Gastropoda Megalobulimus abbreviatus as a useful model for nociceptive experiments: effects of morphine and naloxone on thermal avoidance behavior

We describe the behavior of the snail Megalobulimus abbreviatus upon receiving thermal stimuli and the effects of pretreatment with morphine and naloxone on behavior after a thermal stimulus, in order to establish a useful model for nociceptive experiments. Snails submitted to non-functional (22ºC) and non-thermal hot-plate stress (30ºC) only displayed exploratory behavior. However, the animals submitted to a thermal stimulus (50ºC) displayed biphasic avoidance behavior. Latency was measured from the time the animal was placed on the hot plate to the time when the animal lifted the head-foot complex 1 cm from the substrate, indicating aversive thermal behavior. Other animals were pretreated with morphine (5, 10, 20 mg/kg) or naloxone (2.5, 5.0, 7.5 mg/kg) 15 min prior to receiving a thermal stimulus (50ºC; N = 9 in each group). The results (means ± SD) showed an extremely significant difference in response latency between the group treated with 20 mg/kg morphine (63.18 ± 14.47 s) and the other experimental groups (P < 0.001). With 2.5 mg/kg (16.26 ± 3.19 s), 5.0 mg/kg (11.53 ± 1.64 s) and 7.5 mg/kg naloxone (7.38 ± 1.6 s), there was a significant, not dose-dependent decrease in latency compared to the control (33.44 ± 8.53 s) and saline groups (29.1 ± 9.91 s). No statistically significant difference was found between the naloxone-treated groups. With naloxone plus morphine, there was a significant decrease in latency when compared to all other groups (minimum 64% in the saline group and maximum 83.2% decrease in the morphine group). These results provide evidence of the involvement of endogenous opioid peptides in the control of thermal withdrawal behavior in this snail, and reveal a stereotyped and reproducible avoidance behavior for this snail species, which could be studied in other pharmacological and neurophysiological studies.

Exercise training prevents increased intraocular pressure and sympathetic vascular modulation in an experimental model of metabolic syndrome

The present study aimed to study the effects of exercise training (ET) performed by rats on a 10-week high-fructose diet on metabolic, hemodynamic, and autonomic changes, as well as intraocular pressure (IOP). Male Wistar rats receiving fructose overload in drinking water (100 g/L) were concomitantly trained on a treadmill for 10 weeks (FT group) or kept sedentary (F group), and a control group (C) was kept in normal laboratory conditions. The metabolic evaluation comprised the Lee index, glycemia, and insulin tolerance test (KITT). Arterial pressure (AP) was measured directly, and systolic AP variability was performed to determine peripheral autonomic modulation. ET attenuated impaired metabolic parameters, AP, IOP, and ocular perfusion pressure (OPP) induced by fructose overload (FT vs F). The increase in peripheral sympathetic modulation in F rats, demonstrated by systolic AP variance and low frequency (LF) band (F: 37±2, 6.6±0.3 vs C: 26±3, 3.6±0.5 mmHg2), was prevented by ET (FT: 29±3, 3.4±0.7 mmHg2). Positive correlations were found between the LF band and right IOP (r=0.57, P=0.01) and left IOP (r=0.64, P=0.003). Negative correlations were noted between KITT values and right IOP (r=-0.55, P=0.01) and left IOP (r=-0.62, P=0.005). ET in rats effectively prevented metabolic abnormalities and AP and IOP increases promoted by a high-fructose diet. In addition, ocular benefits triggered by exercise training were associated with peripheral autonomic improvement.

Variance reduction properties of dynamic hedging models - empirical evidence from BRICS countries

This Master’s Thesis analyses the effectiveness of different hedging models on BRICS (Brazil, Russia, India, China, and South Africa) countries. Hedging performance is examined by comparing two different dynamic hedging models to conventional OLS regression based model. The dynamic hedging models being employed are Constant Conditional Correlation (CCC) GARCH(1,1) and Dynamic Conditional Correlation (DCC) GARCH(1,1) with Student’s t-distribution. In order to capture the period of both Great Moderation and the latest financial crisis, the sample period extends from 2003 to 2014. To determine whether dynamic models outperform the conventional one, the reduction of portfolio variance for in-sample data with contemporaneous hedge ratios is first determined and then the holding period of the portfolios is extended to one and two days. In addition, the accuracy of hedge ratio forecasts is examined on the basis of out-of-sample variance reduction. The results are mixed and suggest that dynamic hedging models may not provide enough benefits to justify harder estimation and daily portfolio adjustment. In this sense, the results are consistent with the existing literature.

PERFORMANCE ANALYSIS OF A TACTICAL ASSET ALLOCATION – Evidence from the Black–Litterman model based fixed income portfolio

Over time the demand for quantitative portfolio management has increased among financial institutions but there is still a lack of practical tools. In 2008 EDHEC Risk and Asset Management Research Centre conducted a survey of European investment practices. It revealed that the majority of asset or fund management companies, pension funds and institutional investors do not use more sophisticated models to compensate the flaws of the Markowitz mean-variance portfolio optimization. Furthermore, tactical asset allocation managers employ a variety of methods to estimate return and risk of assets, but also need sophisticated portfolio management models to outperform their benchmarks. Recent development in portfolio management suggests that new innovations are slowly gaining ground, but still need to be studied carefully. This thesis tries to provide a practical tactical asset allocation (TAA) application to the Black–Litterman (B–L) approach and unbiased evaluation of B–L models’ qualities. Mean-variance framework, issues related to asset allocation decisions and return forecasting are examined carefully to uncover issues effecting active portfolio management. European fixed income data is employed in an empirical study that tries to reveal whether a B–L model based TAA portfolio is able outperform its strategic benchmark. The tactical asset allocation utilizes Vector Autoregressive (VAR) model to create return forecasts from lagged values of asset classes as well as economic variables. Sample data (31.12.1999–31.12.2012) is divided into two. In-sample data is used for calibrating a strategic portfolio and the out-of-sample period is for testing the tactical portfolio against the strategic benchmark. Results show that B–L model based tactical asset allocation outperforms the benchmark portfolio in terms of risk-adjusted return and mean excess return. The VAR-model is able to pick up the change in investor sentiment and the B–L model adjusts portfolio weights in a controlled manner. TAA portfolio shows promise especially in moderately shifting allocation to more risky assets while market is turning bullish, but without overweighting investments with high beta. Based on findings in thesis, Black–Litterman model offers a good platform for active asset managers to quantify their views on investments and implement their strategies. B–L model shows potential and offers interesting research avenues. However, success of tactical asset allocation is still highly dependent on the quality of input estimates.

A social-cognitive model of monitoring and its relationship to behaviour in a naturalistic observation : development and individual differences

years 8 months) and 24 older (M == 7 years 4 months) children. A Monitoring Process Model (MPM) was developed and tested in order to ascertain at which component process ofthe MPM age differences would emerge. The MPM had four components: (1) assessment; (2) evaluation; (3) planning; and (4) behavioural control. The MPM was assessed directly using a referential communication task in which the children were asked to make a series of five Lego buildings (a baseline condition and one building for each MPM component). Children listened to instructions from one experimenter while a second experimenter in the room (a confederate) intetjected varying levels ofverbal feedback in order to assist the children and control the component ofthe MPM. This design allowed us to determine at which "stage" ofprocessing children would most likely have difficulty monitoring themselves in this social-cognitive task. Developmental differences were obselVed for the evaluation, planning and behavioural control components suggesting that older children were able to be more successful with the more explicit metacomponents. Interestingly, however, there was no age difference in terms ofLego task success in the baseline condition suggesting that without the intelVention ofthe confederate younger children monitored the task about as well as older children. This pattern ofresults indicates that the younger children were disrupted by the feedback rather than helped. On the other hand, the older children were able to incorporate the feedback offered by the confederate into a plan ofaction. Another aim ofthis study was to assess similar processing components to those investigated by the MPM Lego task in a more naturalistic observation. Together the use ofthe Lego Task ( a social cognitive task) and the naturalistic social interaction allowed for the appraisal of cross-domain continuities and discontinuities in monitoring behaviours. In this vein, analyses were undertaken in order to ascertain whether or not successful performance in the MPM Lego Task would predict cross-domain competence in the more naturalistic social interchange. Indeed, success in the two latter components ofthe MPM (planning and behavioural control) was related to overall competence in the naturalistic task. However, this cross-domain prediction was not evident for all levels ofthe naturalistic interchange suggesting that the nature ofthe feedback a child receives is an important determinant ofresponse competency. Individual difference measures reflecting the children's general cognitive capacity (Working Memory and Digit Span) and verbal ability (vocabulary) were also taken in an effort to account for more variance in the prediction oftask success. However, these individual difference measures did not serve to enhance the prediction oftask performance in either the Lego Task or the naturalistic task. Similarly, parental responses to questionnaires pertaining to their child's temperament and social experience also failed to increase prediction oftask performance. On-line measures ofthe children's engagement, positive affect and anxiety also failed to predict competence ratings.

The Shape of the Risk Premium: Evidence from a Semiparametric Garch Model.

We examine the relationship between the risk premium on the S&P 500 index return and its conditional variance. We use the SMEGARCH - Semiparametric-Mean EGARCH - model in which the conditional variance process is EGARCH while the conditional mean is an arbitrary function of the conditional variance. For monthly S&P 500 excess returns, the relationship between the two moments that we uncover is nonlinear and nonmonotonic. Moreover, we find considerable persistence in the conditional variance as well as a leverage effect, as documented by others. Moreover, the shape of these relationships seems to be relatively stable over time.

Testing Mean-Variance Efficiency in CAPM with Possibly Non-Gaussian Errors : An Exact Simulation-Based Approach

In this paper we propose exact likelihood-based mean-variance efficiency tests of the market portfolio in the context of Capital Asset Pricing Model (CAPM), allowing for a wide class of error distributions which include normality as a special case. These tests are developed in the frame-work of multivariate linear regressions (MLR). It is well known however that despite their simple statistical structure, standard asymptotically justified MLR-based tests are unreliable. In financial econometrics, exact tests have been proposed for a few specific hypotheses [Jobson and Korkie (Journal of Financial Economics, 1982), MacKinlay (Journal of Financial Economics, 1987), Gib-bons, Ross and Shanken (Econometrica, 1989), Zhou (Journal of Finance 1993)], most of which depend on normality. For the gaussian model, our tests correspond to Gibbons, Ross and Shanken’s mean-variance efficiency tests. In non-gaussian contexts, we reconsider mean-variance efficiency tests allowing for multivariate Student-t and gaussian mixture errors. Our framework allows to cast more evidence on whether the normality assumption is too restrictive when testing the CAPM. We also propose exact multivariate diagnostic checks (including tests for multivariate GARCH and mul-tivariate generalization of the well known variance ratio tests) and goodness of fit tests as well as a set estimate for the intervening nuisance parameters. Our results [over five-year subperiods] show the following: (i) multivariate normality is rejected in most subperiods, (ii) residual checks reveal no significant departures from the multivariate i.i.d. assumption, and (iii) mean-variance efficiency tests of the market portfolio is not rejected as frequently once it is allowed for the possibility of non-normal errors.

Le service minimum et les services essentiels : étude française confrontée au droit québécois

"Thèse présentée à la Faculté des études supérieures en vue de l'obtention du grade de Docteur en droit (L.L.D)"