Search results for "Akaike information criterion"
showing 8 items of 18 documents
A computationally fast alternative to cross-validation in penalized Gaussian graphical models
2015
We study the problem of selection of regularization parameter in penalized Gaussian graphical models. When the goal is to obtain the model with good predicting power, cross validation is the gold standard. We present a new estimator of Kullback-Leibler loss in Gaussian Graphical model which provides a computationally fast alternative to cross-validation. The estimator is obtained by approximating leave-one-out-cross validation. Our approach is demonstrated on simulated data sets for various types of graphs. The proposed formula exhibits superior performance, especially in the typical small sample size scenario, compared to other available alternatives to cross validation, such as Akaike's i…
Model comparison and selection for stationary space–time models
2007
An intensive simulation study to compare the spatio-temporal prediction performances among various space-time models is presented. The models having separable spatio-temporal covariance functions and nonseparable ones, under various scenarios, are also considered. The computational performance among the various selected models are compared. The issue of how to select an appropriate space-time model by accounting for the tradeoff between goodness-of-fit and model complexity is addressed. Performances of the two commonly used model-selection criteria, Akaike information criterion and Bayesian information criterion are examined. Furthermore, a practical application based on the statistical ana…
Pharmacokinetics of the cannabinoid receptor ligand [18 F]MK-9470 in the rat brain - Evaluation of models using microPET
2018
PURPOSE The positron emission tomography ligand [18 F]MK-9470 is an inverse agonist that binds reversibly and with high affinity to the cannabinoid type 1 receptor. Due to its slow brain kinetics, care is required in the definition of its dissociation rates from the receptor. The goal of this study was to investigate pharmacokinetic analysis methods using an arterial input function. METHODS Five Sprague-Dawley rats received injections of 13 to 25 MBq of [18 F]MK-9470 and were scanned over a period of 90 min. Arterial blood samples were collected throughout the scan. Data were analyzed using four different compartmental models: a reversible one-tissue model, reversible two tissue models with…
Survival Rates of Young MagpiesPica picain a Mountain Population of Eastern Spain
2007
Abstract. The aim of this study was to estimate the survival of young Magpies between fledging and the next breeding season and to identify some of the factors affecting it. A total of 50 nestlings were colour-ringed in two breeding seasons in the valley of the Pitarque River (Teruel, E Spain), and were monitored weekly until May of the following year. 59 nestlings were also colour-ringed in two nearby localities (4–5 km) to detect possible dispersal to and from our study area. Mark-recapture analyses were used to estimate weekly survival, which was assumed to be constant for periods of four weeks in order to reduce the number of parameters. Models with the effect of time, age class, season…
Artificial Neural Networks for Predicting the Water Retention Curve of Sicilian Agricultural Soils
2018
Modeling soil-water regime and solute transport in the vadose zone is strategic for estimating agricultural productivity and optimizing irrigation water management. Direct measurements of soil hydraulic properties, i.e., the water retention curve and the hydraulic conductivity function, are often expensive and time-consuming, and represent a major obstacle to the application of simulation models. As a result, there is a great interest in developing pedotransfer functions (PTFs) that predict the soil hydraulic properties from more easily measured and/or routinely surveyed soil data, such as particle size distribution, bulk density (&rho
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…
Ecologists overestimate the importance of predictor variables in model averaging: a plea for cautious interpretations.
2014
Abstract: Information-theory procedures are powerful tools for multimodel inference and are now standard methods in ecology. When performing model averaging on a given set of models, the importance of a predictor variable is commonly estimated by summing the weights of models where the variable appears, the so-called sum of weights (SW). However, SWs have received little methodological attention and are frequently misinterpreted. We assessed the reliability of SW by performing model selection and averaging on simulated data sets including variables strongly and weakly correlated to the response variable and a variable unrelated to the response. Our aim was to investigate how useful SWs are …
CALIBRATION OF LÉVY PROCESSES USING OPTIMAL CONTROL OF KOLMOGOROV EQUATIONS WITH PERIODIC BOUNDARY CONDITIONS
2018
We present an optimal control approach to the problem of model calibration for L\'evy processes based on a non parametric estimation procedure. The calibration problem is of considerable interest in mathematical finance and beyond. Calibration of L\'evy processes is particularly challenging as the jump distribution is given by an arbitrary L\'evy measure, which form a infinite dimensional space. In this work, we follow an approach which is related to the maximum likelihood theory of sieves. The sampling of the L\'evy process is modelled as independent observations of the stochastic process at some terminal time $T$. We use a generic spline discretization of the L\'evy jump measure and selec…