Search results for "Heteroscedasticity"
showing 10 items of 29 documents
Bayesian two-stage regression with parametric heteroscedasticity
2008
In this paper, we expand Kleibergen and Zivot's (2003) Bayesian two-stage (B2S) model by allowing for unequal variances. Our choice for modeling heteroscedasticity is a fully Bayesian parametric approach. As an application, we present a cross-country Cobb–Douglas production function estimation.
Retrieval of aboveground crop nitrogen content with a hybrid machine learning method
2020
Abstract Hyperspectral acquisitions have proven to be the most informative Earth observation data source for the estimation of nitrogen (N) content, which is the main limiting nutrient for plant growth and thus agricultural production. In the past, empirical algorithms have been widely employed to retrieve information on this biochemical plant component from canopy reflectance. However, these approaches do not seek for a cause-effect relationship based on physical laws. Moreover, most studies solely relied on the correlation of chlorophyll content with nitrogen, and thus neglected the fact that most N is bound in proteins. Our study presents a hybrid retrieval method using a physically-base…
Warped Gaussian Processes in Remote Sensing Parameter Estimation and Causal Inference
2018
This letter introduces warped Gaussian process (WGP) regression in remote sensing applications. WGP models output observations as a parametric nonlinear transformation of a GP. The parameters of such a prior model are then learned via standard maximum likelihood. We show the good performance of the proposed model for the estimation of oceanic chlorophyll content from multispectral data, vegetation parameters (chlorophyll, leaf area index, and fractional vegetation cover) from hyperspectral data, and in the detection of the causal direction in a collection of 28 bivariate geoscience and remote sensing causal problems. The model consistently performs better than the standard GP and the more a…
Empirical Likelihood-Based ANOVA for Trimmed Means
2016
In this paper, we introduce an alternative to Yuen’s test for the comparison of several population trimmed means. This nonparametric ANOVA type test is based on the empirical likelihood (EL) approach and extends the results for one population trimmed mean from Qin and Tsao (2002). The results of our simulation study indicate that for skewed distributions, with and without variance heterogeneity, Yuen’s test performs better than the new EL ANOVA test for trimmed means with respect to control over the probability of a type I error. This finding is in contrast with our simulation results for the comparison of means, where the EL ANOVA test for means performs better than Welch’s heteroscedastic…
GARCH models with changes in variance: An approximation to risk measurements
2003
This study aims to model volatility as an approximation to an optimum measurement of stock market risk because of the importance of this concept for, among other things, the proper management of portfolios. Following the proposal of Lamoureux and Lastrapes (1990), the authors consider that the high degree of persistence detected in GARCH models arises from a poor specification of the equation of the variance due to not considering the possible deterministic changes in the unconditional variance of the financial series. To determine the point in time as well as the duration of these changes, the proposal made by Inclan and Tiao (1994) is used. As an empirical application, whether or not the …
Biophysical parameter retrieval with warped Gaussian processes
2015
This paper focuses on biophysical parameter retrieval based on Gaussian Processes (GPs). Very often an arbitrary transformation is applied to the observed variable (e.g. chlorophyll content) to better pose the problem. This standard practice essentially tries to linearize/uniformize the distribution by applying non-linear link functions like the logarithmic, the exponential or the logistic functions. In this paper, we propose to use a GP model that automatically learns the optimal transformation directly from the data. The so-called warped GP regression (WGPR) presented in [1] models output observations as a parametric nonlinear transformation of a GP. The parameters of such prior model are…
Experimental Sentinel-2 LAI estimation using parametric, non-parametric and physical retrieval methods – A comparison
2015
Abstract Given the forthcoming availability of Sentinel-2 (S2) images, this paper provides a systematic comparison of retrieval accuracy and processing speed of a multitude of parametric, non-parametric and physically-based retrieval methods using simulated S2 data. An experimental field dataset (SPARC), collected at the agricultural site of Barrax (Spain), was used to evaluate different retrieval methods on their ability to estimate leaf area index (LAI). With regard to parametric methods, all possible band combinations for several two-band and three-band index formulations and a linear regression fitting function have been evaluated. From a set of over ten thousand indices evaluated, the …
On the moments of Cochran's Q statistic under the null hypothesis, with application to the meta-analysis of risk difference.
2011
W. G. Cochran's Q statistic was introduced in 1937 to test for equality of means under heteroscedasticity. Today, the use of Q is widespread in tests for homogeneity of effects in meta-analysis, but often these effects (such as risk differences and odds ratios) are not normally distributed. It is common to assume that Q follows a chi-square distribution, but it has long been known that this asymptotic distribution for Q is not accurate for moderate sample sizes. In this paper, the effect and weight for an individual study may depend on two parameters: the effect and a nuisance parameter. We present expansions for the first two moments of Q without any normality assumptions. Our expansions w…
Uncertainty and Equifinality in Calibrating Distributed Roughness Coefficients in a Flood Propagation Model with Limited Data
1998
Monte-Carlo simulations of a two-dimensional finite element model of a flood in the southern part of Sicily were used to explore the parameter space of distributed bed-roughness coefficients. For many real-world events specific data are extremely limited so that there is not only fuzziness in the information available to calibrate the model, but fuzziness in the degree of acceptability of model predictions based upon the different parameter values, owing to model structural errors. Here the GLUE procedure is used to compare model predictions and observations for a certain event, coupled with both a fuzzy-rule-based calibration, and a calibration technique based upon normal and heteroscedast…
Testing for Financial Contagion Between Developed and Emerging Markets During the 1997 East Asian Crisis
2003
In this paper we examine whether during the 1997 East Asian crisis there was any contagion from the four largest economies in the region (Thailand, Indonesia, Korea and Malaysia) to a number of developed countries (Japan, UK, Germany and France). Following Forbes and Rigobon (2002), we test for contagion as a significant positive shift in the correlation between asset returns, taking into account heteroscedasticity and endogeneity bias. Furthermore, we improve on earlier empirical studies by carrying out a full sample test of the stability of the system that relies on more plausible (over)identifying restrictions. The estimation results provide some evidence of contagion, in particular from…