scholarly journals A Functional Information Criterion for Region Selection in Functional Linear Models

2022 ◽  
Author(s):  
Yunxiang Huang ◽  
Qihua Wang
Keyword(s):  
Linear Models ◽  
Information Criterion ◽  
Functional Information ◽  
Functional Linear Models ◽  
Region Selection

scholarly journals The Optimal Selection for Restricted Linear Models with Average Estimator

2014 ◽  
Vol 2014 ◽  
pp. 1-13
Author(s):  
Qichang Xie ◽  
Meng Du
Keyword(s):  
Model Selection ◽  
Linear Models ◽  
Weighted Average ◽  
Selection Procedure ◽  
Information Criterion ◽  
Optimal Weights ◽  
Model Average ◽  
Squared Error ◽  
Generalized Information Criterion ◽  
Risk Investment

The essential task of risk investment is to select an optimal tracking portfolio among various portfolios. Statistically, this process can be achieved by choosing an optimal restricted linear model. This paper develops a statistical procedure to do this, based on selecting appropriate weights for averaging approximately restricted models. The method of weighted average least squares is adopted to estimate the approximately restricted models under dependent error setting. The optimal weights are selected by minimizing ak-class generalized information criterion (k-GIC), which is an estimate of the average squared error from the model average fit. This model selection procedure is shown to be asymptotically optimal in the sense of obtaining the lowest possible average squared error. Monte Carlo simulations illustrate that the suggested method has comparable efficiency to some alternative model selection techniques.

scholarly journals A global scientific literature of research on water quality indices: trends, biases and future directions

2014 ◽  
Vol 26 (3) ◽  
pp. 245-253 ◽  
Author(s):  
Maria Tereza Ribeiro Alves ◽  
Fabrício Barreto Teresa ◽  
João Carlos Nabout
Keyword(s):  
Water Quality ◽  
Linear Models ◽  
Scientific Literature ◽  
Information Criterion ◽  
The United States ◽  
Water Index ◽  
Resource Managers ◽  
Quality Of Water ◽  
Number Of Publications

AIM: Water quality has been the subject of many recent studies, moreover, the physical, chemical and biological parameters of water are used to investigate water quality and can be combined into a single index, the Water Quality Index (WQI), for use by water resource managers and the general public. The aim of this study was to use scientometrics to evaluate how water quality has been addressed in the international scientific literature. METHOD: For the quantitative analysis of the publications on WQI, we used the search database SCOPUS (http://www.scopus.com). The search was performed using the words "QUALIT* WATER* INDEX*" in papers published in all databases (through 2011). RESULTS: We found 554 articles that dealt with the use of WQI the number of publications has increased significantly over the last 20 years. India had the most studies, with 177 articles, followed by China, Brazil and the United States. These four countries together published 57% of studies on WQI. We generated 15 linear models to explain the number of publication by study sit (country). According to the Akaike Information Criterion (AIC), the best model to explain the number of publications by country was the model that combined Sanitation and Public Supply. CONCLUSION: Finally, this paper presents the state of scientific literature on WQI and demonstrates the growing interest of the scientific community in this issue, which is certainly due to the importance of the quantity and quality of water for human supply, economics, health and the conservation of water resources.

scholarly journals Nonlinear modeling growth body weight of Mangalarga Marchador horses

2017 ◽  
Vol 47 (4) ◽  
Author(s):  
Felipe Amorim Caetano Souza ◽  
Tales Jesus Fernandes ◽  
Raquel Silva de Moura ◽  
Sarah Laguna Conceição Meirelles ◽  
Rafaela Aparecida Ribeiro ◽  
...  
Keyword(s):  
Body Weight ◽  
Linear Models ◽  
Nonlinear Modeling ◽  
Growth Curves ◽  
Live Weight ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Cross Sectional ◽  
Adult Body Weight ◽  
The Cross

ABSTRACT: The analysis of the growth and development of various species has been done using the growth curves of the specific animal based on non-linear models. The objective of the current study was to evaluate the fit of the Brody, Gompertz, Logistic and von Bertalanffy models to the cross-sectional data of the live weight of the MangalargaMarchador horses to identify the best model and make accurate predictions regarding the growth and maturity in the males and females of this breed. The study involved recording the weight of 214 horses, of which 94 were males and 120 were non-pregnant females, between 6 and 153 months of age. The parameters of the model were estimated by employing the method of least squares, using the iteratively regularized Gauss-Newton method and the R software package. Comparison of the models was done based on the following criteria: coefficient of determination (R²); Residual Standard Deviation (RSD); corrected Akaike Information Criterion (AICc). The estimated weight of the adult horses by the models ranged between 431kg and 439kg for males and between 416kg and 420kg for females. The growth curves were studied using the cross-sectional data collection method. For males the von Bertalanffymodel was found to be the most effective in expressing growth, while in females the Brody model was more suitable. The MangalargaMarchador females achieve adult body weight earlier than the males.

scholarly journals Quantifying flow–ecology relationships with functional linear models

2014 ◽  
Vol 59 (3-4) ◽  
pp. 629-644 ◽  
Author(s):  
Ben Stewart-Koster ◽  
Julian D. Olden ◽  
Keith B. Gido
Keyword(s):  
Linear Models ◽  
Functional Linear Models

scholarly journals DELINEATION OF HOMOGENEOUS ZONES BASED ON GEOSTATISTICAL MODELS ROBUST TO OUTLIERS

2019 ◽  
Vol 32 (2) ◽  
pp. 472-481
Author(s):  
DANILO PEREIRA BARBOSA ◽  
EDUARDO LEONEL BOTTEGA ◽  
DOMINGOS SÁRVIO MAGALHÃES VALENTE ◽  
NERILSON TERRA SANTOS ◽  
WELLINGTON DONIZETE GUIMARÃES
Keyword(s):  
Linear Models ◽  
Information Criterion ◽  
Physicochemical Characteristics ◽  
Parameter Estimates ◽  
Mixed Linear Models ◽  
Management Zones ◽  
Geostatistical Models ◽  
Apparent Electrical Conductivity ◽  
External Drift ◽  
Theory And Model

ABSTRACT Measures of the apparent electrical conductivity (ECa) of soil are used in many studies as indicators of spatial variability in physicochemical characteristics of production fields. Based on these measures, management zones (MZs) are delineated to improve agricultural management. However, these measures include outliers. The presence or incorrect identification and exclusion of outliers affect the variogram function and result in unreliable parameter estimates. Thus, the aim of this study was to model ECa data with outliers using methods based on robust approximation theory and model-based geostatistics to delineate MZs. Robust estimators developed by Cressie-Hawkins, Genton and MAD Dowd were tested. The Cressie-Hawkins semivariance estimator was selected, followed by the semivariogram cubic fit using Akaike information criterion (AIC). The robust kriging with an external drift plug-in was applied to fitted estimates, and the fuzzy k-means classifier was applied to the resulting ECa kriging map. Models with multiple MZs were evaluated using fuzzy k-means, and a map with two MZs was selected based on the fuzzy performance index (FPI), modified partition entropy (MPE) and Fukuyama-Sugeno and Xie-Beni indices. The defined MZs were validated based on differences between the ECa means using mixed linear models. The independent errors model was chosen for validation based on its AIC value. Thus, the results demonstrate that it is possible to delineate an MZ map without outlier exclusion, evidencing the efficacy of this methodology.

scholarly journals Prerecruit survival and recruitment of northern Gulf of St Lawrence Atlantic cod

2008 ◽  
Vol 65 (6) ◽  
pp. 946-952 ◽  
Author(s):  
Daniel E. Duplisea ◽  
Dominique Robert
Keyword(s):  
Linear Models ◽  
Atlantic Cod ◽  
Information Criterion ◽  
Factors Affecting ◽  
Control Rules ◽  
Strategy Evaluation ◽  
Stock Biomass ◽  
Spawning Stock ◽  
Long Time ◽  
Parsimonious Model

Abstract Duplisea, D. E., and Robert, D. 2008. Prerecruit survival and recruitment of northern Gulf of St Lawrence Atlantic cod. – ICES Journal of Marine Science, 65: 946–952. Recruitment (R) of exploited marine fish populations is usually modelled exclusively as a function of spawning-stock biomass (SSB). A problem arising when modelling over long time-series is that the nature of the R–SSB relationship is unlikely to be stationary. Changes are often interpreted as productivity regime shifts and are linked to alterations in prerecruit survival rate. We examine the role of environment and predation by fish and harp seals as factors affecting the R–SSB relationship in the northern Gulf of St Lawrence cod, by fitting linear models using combinations of covariates to explain cod prerecruit survival. The most parsimonious model (based on a Bayesian Information Criterion, BIC) included cod, mackerel, and temperature, whereas redfish and seals did not appear in any of the best-fit models. Recruitment models derived from this analysis could be used in operating models for management strategy evaluation simulations for northern Gulf cod, so one could develop harvest control rules that are robust to changes in recruitment productivity regimes.

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