Search results for "Additive model"
showing 10 items of 28 documents
On the thermodynamic origin of metabolic scaling
2018
The origin and shape of metabolic scaling has been controversial since Kleiber found that basal metabolic rate of animals seemed to vary as a power law of their body mass with exponent 3/4, instead of 2/3, as a surface-to-volume argument predicts. The universality of exponent 3/4 -claimed in terms of the fractal properties of the nutrient network- has recently been challenged according to empirical evidence that observed a wealth of robust exponents deviating from 3/4. Here we present a conceptually simple thermodynamic framework, where the dependence of metabolic rate with body mass emerges from a trade-off between the energy dissipated as heat and the energy efficiently used by the organi…
Assessing the importance of nursery areas of European hake (Merluccius merluccius) using a body condition index
2017
Abstract In this study, we analysed the variability of reserve storage in juvenile European hake (Merluccius merluccius) off the western coasts of Italy (Central Mediterranean Sea). Reserve storage was measured by the hepatosomatic index (HSI), in relation to environmental and population covariates. HSI has been proved to be a consistent measure of energy storage in gadoids, thus reflecting quantity and quality of food availability for growth. Generalized Additive Models for Location, Scale and Shape (GAMLSS) were used to model the effect of depth, bottom temperature, bottom currents, fish density and fish body size on HSI of juvenile European hake. The results revealed that reserve storage…
Assessing Spillover Effects of Spatial Policies with Semiparametric Zero-Inflated Models and Random Forests
2021
The aim of this work is to estimate the variation over time of the spatial spillover effects of a public policy that was devoted to boost rural development in France over the period 1993–2002. At a micro data level, it is often observed that the dependent variable, such as local employment in a municipality, does not vary along time, so that we face a kind of zero inflated phenomenon that cannot be dealt with a classical continuous response model or propensity score approaches. We consider two recent non parametric techniques that are able to deal with that estimation issue. The first approach consists in fitting two generalized additive models to estimate both the probability of no variati…
Modelling of Adequate Costs of Utilities Services
2016
The paper propose methodology for benchmark modelling of adequate costs of utilities services, which is based on the data analysis of the factual cases (key performance indicators of utilities as the predictors). The proposed methodology was tested by modelling of Latvian water utilities with three tools: (1) a classical version of the multi-layer perceptron with error back-propagation training algorithm was sharpened up with task-specific monotony tests, (2) the fitting of the generalized additive model using the programming language R ensured the opportunity to evaluate the statistical significance and confidence bands of predictors, (3) the sequential iterative nonlinear regression proce…
Optimal designs for a one-way layout with covariates
2000
Abstract For the general class of Φ q -criteria optimal designs are characterized which reflect the inherent symmetry in a one-way layout with covariates. In particular, the eigenvalues of the covariance matrices are related to those in suitably chosen marginal models depending on the underlying interaction structure.
Forecasting time series with missing data using Holt's model
2009
This paper deals with the prediction of time series with missing data using an alternative formulation for Holt's model with additive errors. This formulation simplifies both the calculus of maximum likelihood estimators of all the unknowns in the model and the calculus of point forecasts. In the presence of missing data, the EM algorithm is used to obtain maximum likelihood estimates and point forecasts. Based on this application we propose a leave-one-out algorithm for the data transformation selection problem which allows us to analyse Holt's model with multiplicative errors. Some numerical results show the performance of these procedures for obtaining robust forecasts.
Modeling temporal treatment effects with zero inflated semi-parametric regression models: The case of local development policies in France
2017
International audience; A semi-parametric approach is proposed to estimate the variation along time of the effects of two distinct public policies that were devoted to boost rural development in France over a similar period of time. At a micro data level, it is often observed that the dependent variable, such as local employment, does not vary along time, so that we face a kind of zero inflated phenomenon that cannot be dealt with a continuous response model. We introduce a conditional mixture model which combines a mass at zero and a continuous response. The suggested zero inflated semi-parametric statistical approach relies on the flexibility and modularity of additive models with the abi…
Comparing cetacean abundance estimates derived from spatial models and design-based line transect methods
2007
Spatial modelling is increasingly being used as an alternative to conventional design- based line transect sampling to estimate cetacean abundance. This new method combines line transect sampling with spatial analysis to predict animal abundance based on the relationship of ani- mals observed to environmental factors. It presents several advantages including: (1) the ability to use data collected from 'platforms of opportunity', (2) the ability to estimate abundance for any defined subarea within the study area, and (3) the possibility for increased precision if covariates explain sufficient variability in the data. One study has been conducted to compare spatial modelling with conventional…
Revealing Hidden Curvilinear Relations Between Work Engagement and Its Predictors: Demonstrating the Added Value of Generalized Additive Model (GAM)
2014
Previous studies measuring different aspects of the quality of life have, as a rule, presumed linear relationships between a dependent variable and its predictors. This article utilizes non-parametric statistical methodology to explore curvilinear relations between work engagement and its main predictors: job demands, job control and social support. Firstly, the study examines what additional information non-linear modeling can reveal regarding the relationship between work engagement and the three predictors in question. Secondly, the article compares the explanatory power of non-linear and linear modeling with regard to work engagement. The generalized additive model (GAM), that makes pos…
An Additive Model to Predict the Rheological and Mechanical Properties of Polypropylene Blends Made by Virgin and Reprocessed Components
2021
In this work, an additive model for the prediction of the rheological and mechanical properties of monopolymer blends made by virgin and reprocessed components is proposed. A polypropylene sample has been reprocessed more times in an extruder and monopolymer blends have been prepared by simulating an industrial process. The scraps are exposed to regrinding and are melt reprocessed before mixing with the virgin polymer. The reprocessed polymer is, then, subjected to some thermomechanical degradation. Rheological and mechanical experimental data have been compared with the theoretical predictions. The results obtained showed that the values of this simple additive model are a very good fit fo…