DELINEATION OF HOMOGENEOUS ZONES BASED ON GEOSTATISTICAL MODELS ROBUST TO OUTLIERS

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.

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Choice of non-linear models to determine the growth curve of meat-type quail

Ciência Rural ◽

10.1590/0103-8478cr20190990 ◽

2021 ◽

Vol 51 (2) ◽

Author(s):

Marta Jeidjane Borges Ribeiro ◽

Fabyano Fonseca Silva ◽

Maíse dos Santos Macário ◽

José Aparecido Santos de Jesus ◽

Claudson Oliveira Brito ◽

...

Keyword(s):

Goodness Of Fit ◽

Linear Models ◽

Growth Curves ◽

Information Criterion ◽

Metabolizable Energy ◽

Coefficient Of Determination ◽

Parameter Estimates ◽

Coturnix Coturnix ◽

Non Linear ◽

Meat Type

ABSTRACT: The objective of this study was to compare non-linear models fitted to the growth curves of quail to determine which model best describes their growth and check the similarity between models by analyzing parameter estimates.Weight and age data of meat-type European quail (Coturnix coturnix coturnix) of three lines were used, from an experiment in a 2 × 4 factorial arrangement in a completely randomized design, consisting of two metabolizable energy levels, four crude protein levels and six replicates. The non-linear Brody, Von Bertalanffy, Richards, Logistic and Gompertz models were used. To choose the best model, the Adjusted Coefficient of Determination, Convergence Rate, Residual Mean Square, Durbin-Watson Test, Akaike Information Criterion and Bayesian Information Criterion were applied as goodness-of-fit indicators. Cluster analysis was performed to check the similarity between models based on the mean parameter estimates. Among the studied models, Richards’ was the most suitable to describe the growth curves. The Logistic and Richards models were considered similar in the analysis with no distinction of lines as well as in the analyses of Lines 1, 2 and 3.

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Determination of the best non-linear function to describe the growth of Kajli sheep

South African Journal of Animal Science ◽

10.4314/sajas.v50i3.12 ◽

2020 ◽

Vol 50 (3) ◽

pp. 452-459

Author(s):

A. Ali ◽

K. Javed ◽

I. Zahoor ◽

K.M. Anjum

Keyword(s):

Linear Function ◽

Goodness Of Fit ◽

Linear Models ◽

Information Criterion ◽

Linear Functions ◽

Coefficient Of Determination ◽

Parameter Estimates ◽

Early Maturity ◽

Linear Pattern ◽

Non Linear

The aim of the present study was to determine the best non-linear growth function to describe the growth of Kajli sheep. For this aim, the Brody, von Bertalanffy, Logistic, and Gompertz models were used to describe the sigmoidal relationship between bodyweight and age of the Kajli sheep. The records obtained from the Livestock Experiment Station, Khushab, were collected between 2007 and 2018. The records comprised 9864 age-weight observations (300 for male, 9564 for female, 7392 for single, 2388 for twin, and 84 for triplet lambs), which extended from birth to 12 months old. Candidate non-linear functions were fitted and the curve parameters were estimated by nlsfit (fit non-linear models) function in R statistical package, version 3.6.1. Goodness of fit criteria that were used to evaluate predictive performances of candidate models were adjusted coefficient of determination (R2adj), Akaike’s information criterion (AIC), Bayesian information criterion (BIC) and root means square error (RMSE). The Brody model was the best non-linear function that described the biological growth pattern of all, male, female, single, twin, and triplet lambs. Differences in curve parameter estimates between male and female suggested a definite pattern of sexual dimorphism. Moreover, a higher estimate of rate of maturity in female lambs reflects their early maturity compared with male Kajli lambs. Similarly, the single-born Kajli animals with highest maturity rate were maturing at an earlier age than twins and triplets. This is the first report on the non-linear pattern of visible changes in bodyweight of Kajli sheep from birth to 12 months old.Key words: age, bodyweight, growth curves, regression, sheep

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Inheritance and Correlation Analysis of Main Agronomic Traits in Mungbean (Vigna radiata L.) by Mixed Linear Models

ACTA AGRONOMICA SINICA ◽

10.3724/sp.j.1006.2012.00624 ◽

2013 ◽

Vol 38 (4) ◽

pp. 624-631

Author(s):

Chang-You LIU ◽

Bao-Jie FAN ◽

Zhi-Min CAO ◽

Yan WANG ◽

Zhi-Xiao ZHANG ◽

...

Keyword(s):

Correlation Analysis ◽

Vigna Radiata ◽

Linear Models ◽

Agronomic Traits ◽

Mixed Linear Models

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Maximum Likelihood Analysis of Rare Binary Traits Under Different Modes of Inheritance

Genetics ◽

10.1093/genetics/143.4.1819 ◽

1996 ◽

Vol 143 (4) ◽

pp. 1819-1829 ◽

Cited By ~ 2

Author(s):

G Thaller ◽

L Dempfle ◽

I Hoeschele

Keyword(s):

Maximum Likelihood ◽

Mixed Model ◽

Major Gene ◽

Likelihood Ratio Statistic ◽

Information Criterion ◽

Genetic Models ◽

Parameter Estimates ◽

Gene Effects ◽

Binary Traits ◽

Deterministic Algorithms

Abstract Maximum likelihood methodology was applied to determine the mode of inheritance of rare binary traits with data structures typical for swine populations. The genetic models considered included a monogenic, a digenic, a polygenic, and three mixed polygenic and major gene models. The main emphasis was on the detection of major genes acting on a polygenic background. Deterministic algorithms were employed to integrate and maximize likelihoods. A simulation study was conducted to evaluate model selection and parameter estimation. Three designs were simulated that differed in the number of sires/number of dams within sires (10/10, 30/30, 100/30). Major gene effects of at least one SD of the liability were detected with satisfactory power under the mixed model of inheritance, except for the smallest design. Parameter estimates were empirically unbiased with acceptable standard errors, except for the smallest design, and allowed to distinguish clearly between the genetic models. Distributions of the likelihood ratio statistic were evaluated empirically, because asymptotic theory did not hold. For each simulation model, the Average Information Criterion was computed for all models of analysis. The model with the smallest value was chosen as the best model and was equal to the true model in almost every case studied.

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