918 resultados para Conditional and Unconditional Interval Estimator


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2000 Mathematics Subject Classification: 62F25, 62F03.

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We studied the effects of repeated stimulation by recombinant human FSH (rhFSH) at various time intervals during a physiologic breeding season in rhesus monkeys. Ovarian recovery and responses were assessed by ultrasonography, serum steroid concentrations

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This study, which is based on 10 years of birth records, shows that black-and-white snub-nosed monkeys (Rhinopithecus bieti) in captivity display marked birth seasonality. The birth season starts in December and ends in June, with a peak from March to May

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We propose a new approach for modeling nonlinear multivariate interest rate processes based on time-varying copulas and reducible stochastic differential equations (SDEs). In the modeling of the marginal processes, we consider a class of nonlinear SDEs that are reducible to Ornstein--Uhlenbeck (OU) process or Cox, Ingersoll, and Ross (1985) (CIR) process. The reducibility is achieved via a nonlinear transformation function. The main advantage of this approach is that these SDEs can account for nonlinear features, observed in short-term interest rate series, while at the same time leading to exact discretization and closed-form likelihood functions. Although a rich set of specifications may be entertained, our exposition focuses on a couple of nonlinear constant elasticity volatility (CEV) processes, denoted as OU-CEV and CIR-CEV, respectively. These two processes encompass a number of existing models that have closed-form likelihood functions. The transition density, the conditional distribution function, and the steady-state density function are derived in closed form as well as the conditional and unconditional moments for both processes. In order to obtain a more flexible functional form over time, we allow the transformation function to be time varying. Results from our study of U.S. and UK short-term interest rates suggest that the new models outperform existing parametric models with closed-form likelihood functions. We also find the time-varying effects in the transformation functions statistically significant. To examine the joint behavior of interest rate series, we propose flexible nonlinear multivariate models by joining univariate nonlinear processes via appropriate copulas. We study the conditional dependence structure of the two rates using Patton (2006a) time-varying symmetrized Joe--Clayton copula. We find evidence of asymmetric dependence between the two rates, and that the level of dependence is positively related to the level of the two rates. (JEL: C13, C32, G12) Copyright The Author 2010. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org, Oxford University Press.

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Financial integration has been pursued aggressively across the globe in the last fifty years; however, there is no conclusive evidence on the diversification gains (or losses) of such efforts. These gains (or losses) are related to the degree of comovements and synchronization among increasingly integrated global markets. We quantify the degree of comovements within the integrated Latin American market (MILA). We use dynamic correlation models to quantify comovements across securities as well as a direct integration measure. Our results show an increase in comovements when we look at the country indexes, however, the increase in the trend of correlation is previous to the institutional efforts to establish an integrated market in the region. On the other hand, when we look at sector indexes and an integration measure, we find a decreased in comovements among a representative sample of securities form the integrated market.

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Two experiments implement and evaluate a training scheme for learning to apply frequency formats to probability judgements couched in terms of percentages. Results indicate that both conditional and cumulative probability judgements can be improved in this manner, however the scheme is insufficient to promote any deeper understanding of the problem structure. In both experiments, training on one problem type only (either conditional or cumulative risk judgements) resulted in an inappropriate transfer of a learned method at test. The obstacles facing a frequency-based training programme for teaching appropriate use of probability data are discussed. Copyright (c) 2006 John Wiley & Sons, Ltd.

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When considering the relative fast processing speed and low power requirements for Wireless Personal Area Networks (WPAN) and Wireless Universal Serial Bus (USB) consumer based products, then the efficiency and cost effectiveness of these products become paramount. This paper presents an improved soft-output QPSK demapper suitable for the products above that not only exploits time diversity and guard carrier diversity, but also merges the demapping and symbol combining functions together to minimize CPU cycles, or memory access dependant upon the chosen implementation architecture. The proposed demapper is presented in the context of Multiband OFDM version of UWB (ECMA-368) as the chosen physical implementation for high-rate Wireless USB.

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When considering the relative fast processing speeds and low power requirements for Wireless Personal Area Networks (WPAN) including Wireless Universal Serial Bus (WUSB) consumer based products, then the efficiency and cost effectiveness of these products become paramount. This paper presents an improved soft-output QPSK demapper suitable for the products above that not only exploits time diversity and guard carrier diversity, but also merges the demapping and symbol combining functions together to minimize CPU cycles, or memory access dependant upon the chosen implementation architecture. The proposed demapper is presented in the context of Multiband OFDM version of Ultra Wideband (UWB) (ECMA-368) as the chosen physical implementation for high-rate Wireless US8(1).

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A modified version of the social habituation/dis-habituation paradigm was employed to examine social recognition memory in Wistar rats during two opposing (active and inactive) circadian phases, using different intertrial intervals (30 and 60 min). Wheel-running activity was monitored continuously to identify circadian phase. To avoid possible masking effects of the light-dark cycle, the rats were synchronized to a skeleton photoperiod, which allowed testing during different circadian phases under identical lighting conditions. In each trial, an infantile intruder was introduced into an adult`s home-cage for a 5-minute interaction session, and social behaviors were registered. Rats were exposed to 5 trials per day for 4 consecutive days: oil days I and 2, each resident was exposed to the same intruder; on days 3 and 4, each resident was exposed to a different intruder in each trial. I he resident`s social investigatory behavior was more intense when different intruders were presented compared to repeated presentation of the same intruder, suggesting social recognition memory. This effect was stronger when the rats were tested during the inactive phase and when the intertrial interval was 60 min, These findings Suggest that social recognition memory, as evaluated in this modified habituation/dis-habituation paradigm, is influenced by the circadian rhythm phase during which testing is performed, and by intertrial interval. (C) 2008 Elsevier Inc. All rights reserved.

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We present a new version (> 2.0) of the hglm package for fitting hierarchical generalized linear models (HGLMs) with spatially correlated random effects. CAR() and SAR() families for conditional and simultaneous autoregressive random effects were implemented. Eigen decomposition of the matrix describing the spatial structure (e.g., the neighborhood matrix) was used to transform the CAR/SAR random effects into an independent, but eteroscedastic, Gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR and SAR models. This gives a computationally efficient algorithm for moderately sized problems.

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In this paper, we have calculated the masses of mesons containing t-quark and their spins' coupling coefficients. This was achieved by solving Lippmann-Schwinger equation for the quark-antiquark bound state of heavy mesons in configuration space. Heavy meson masses submitted criteria for the strong nuclear interactive potential between two quarks. We investigated the stability of a few suitable potentials and offered the best of these potentials for heavy mesons.