Search results for "Akaike information criterion"
showing 10 items of 18 documents
Real wages-employment relationship in Finnish manufacturing: a VAR approach
1991
Granger's concept of causality and the vector autoregressive(VAR) technique is used to investigate the real wages-employment relationship in Finnish manufacturing. The stationarity of the time series is examined and a number of co-integration tests for the adequacy of a pure VAR specification performed. The results using a bivariate VAR model based on a lag structure determined by Akaike's information criterion suggests that real wages Granger-cause employment. The slight non-constancy of the model suggests, however, that the conclusion concerning the nature of the real wages-emploment relationship should be treated with causion.
Spatial autocorrelation and the selection of simultaneous autoregressive models
2007
Aim Spatial autocorrelation is a frequent phenomenon in ecological data and can affect estimates of model coefficients and inference from statistical models. Here, we test the performance of three different simultaneous autoregressive (SAR) model types (spatial error = SAR err , lagged = SAR lag and mixed = SAR mix ) and common ordinary least squares (OLS) regression when accounting for spatial autocorrelation in species distribution data using four artificial data sets with known (but different) spatial autocorrelation structures. Methods We evaluate the performance of SAR models by examining spatial patterns in model residuals (with correlograms and residual maps), by comparing model para…
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…
Habitat preferences of edible dormouse, Glis glis italicus: implications for the management of arboreal mammals in Mediterranean forests
2015
Research on arboreal mammals living in Mediterranean forests is poor. Molecular research assessed the existence of an evolutionary significant unit in the edible dormouse populations living in south Italy, Sicily and Sardinia, and we decided to investigate the environmental factors capable of explaining its occurrence and abundance in Sicily, for a better management of these populations. We assessed the species habitat preferences by setting 25 large and 25 small nestboxes in five sample areas along an altitudinal gradient of the Madonie Range, and recorded habitat variables, food availability, and demographic data for two years. To obtain synthetic descriptors of the dormice habitat requir…
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…
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…
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…
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
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 …
EMG, heart rate, and accelerometer as estimators of energy expenditure in locomotion.
2014
AB Purpose: Precise measures of energy expenditure (EE) during everyday activities are needed. This study assessed the validity of novel shorts measuring EMG and compared this method with HR and accelerometry (ACC) when estimating EE. Methods: Fifty-four volunteers (39.4 +/- 13.9 yr) performed a maximal treadmill test (3-min loads) including walking with different speeds uphill, downhill, and on level ground and one running load. The data were categorized into all, low, and level loads. EE was measured by indirect calorimetry, whereas HR, ACC, and EMG were measured continuously. EMG from quadriceps (Q) and hamstrings (H) was measured using shorts with textile electrodes. Validity of the met…