Search results for "Homoscedasticity"
showing 7 items of 7 documents
An alternative conception of PM10 concentration changes after short-term precipitation in urban environment
2018
Abstract In the article, a linear model is presented which describes a reduction of PM10 mass concentration in relation to the type of precipitation and water vapour content in the air. The model was built using covariance analysis. In studies of PM10 concentration changes, the results of 247 observations were used, which were carried out in the urban area. Concentration changes were archived during short-term (30 min) convection and large-scale rainfalls. For the determination of PM10 mass concentration, the reference method was used. To describe changes in PM10 concentration in the air after precipitation, a series of linear models were created, in which the explanatory variables were: th…
Uncertainty estimation of a complex water quality model: The influence of Box–Cox transformation on Bayesian approaches and comparison with a non-Bay…
2012
Abstract In urban drainage modelling, uncertainty analysis is of undoubted necessity. However, uncertainty analysis in urban water-quality modelling is still in its infancy and only few studies have been carried out. Therefore, several methodological aspects still need to be experienced and clarified especially regarding water quality modelling. The use of the Bayesian approach for uncertainty analysis has been stimulated by its rigorous theoretical framework and by the possibility of evaluating the impact of new knowledge on the modelling predictions. Nevertheless, the Bayesian approach relies on some restrictive hypotheses that are not present in less formal methods like the Generalised L…
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…
Risk forecasting models and optimal portfolio selection
2005
This study analyses, from an investor's perspective, the performance of several risk forecasting models in obtaining optimal portfolios. The plausibility of the homoscedastic hypothesis implied in the classical Markowitz model is dicussed and more general models which take into account assymetry and time varying risk are analysed. Specifically, it studies whether ARCH-type based models obtain portfolios whose risk-adjusted returns exceed those of the classical Markowitz model. The same analysis is performed with models based on the Lower Partial Moment (LPM) which take into account the assymetry in the distribution of returns. The results suggest that none of the models achieve a clearly su…
Holt–Winters Forecasting: An Alternative Formulation Applied to UK Air Passenger Data
2007
Abstract This paper provides a formulation for the additive Holt–Winters forecasting procedure that simplifies both obtaining maximum likelihood estimates of all unknowns, smoothing parameters and initial conditions, and the computation of point forecasts and reliable predictive intervals. The stochastic component of the model is introduced by means of additive, uncorrelated, homoscedastic and Normal errors, and then the joint distribution of the data vector, a multivariate Normal distribution, is obtained. In the case where a data transformation was used to improve the fit of the model, cumulative forecasts are obtained here using a Monte-Carlo approximation. This paper describes the metho…
On the convenience of heteroscedasticity in highly multivariate disease mapping
2019
Highly multivariate disease mapping has recently been proposed as an enhancement of traditional multivariate studies, making it possible to perform the joint analysis of a large number of diseases. This line of research has an important potential since it integrates the information of many diseases into a single model yielding richer and more accurate risk maps. In this paper we show how some of the proposals already put forward in this area display some particular problems when applied to small regions of study. Specifically, the homoscedasticity of these proposals may produce evident misfits and distorted risk maps. In this paper we propose two new models to deal with the variance-adaptiv…
Analysis of Relationship between Net Wage and Consumer Price Index
2013
Abstract In the present paper is presented an econometric analysis of the relationship between net salary and consumer price index. After a brief historical overview will be review the calculating statistics for selected variables and coefficients and will be presented the obtained values. We will study the relationship between variables. It will be realized the cloud of points and will be applied Fisher test. The intensity of selected variables will be study too and some forms of relationship between the two chose variables will be done. Student test is applied. It will be performed the parameter estimation for regression functions and Akaike's criterion will be applied. The homoscedastici…