scholarly journals Estimation of diurnal total radiation based on meteorological variables in the period of plant vegetation in Poland

2018 ◽  
Vol 23 ◽  
pp. 00032 ◽  
Author(s):  
Paulina Stanek ◽  
Leszek Kuchar ◽  
Irena Otop
Keyword(s):  
Relative Error ◽  
Linear Models ◽  
Meteorological Data ◽  
The Other ◽  
Meteorological Variables ◽  
Coefficient Of Determination ◽  
Total Radiation ◽  
Radiation Data ◽  
Non Linear ◽  
Best Fit

The paper presents selected models for the estimation of diurnal total radiation on the basis of other meteorological variables (using simple data as temperature and rainfall) in the vegetation months in the territory of Poland. For that purpose 6 meteorological stations were selected, having standard meteorological data as well as total radiation data for the period of 2001 – 2010. The stations were chosen so that two of them were situated on the coast, two in the lowland part of the country, and two in the mountains. The models were evaluated with the use of the coefficient of determination R² and the relative error of estimation RMSE with division into 6 months and 6 meteorological stations. In each of the regions the best results were obtained for models 6 and 7 which are combinations of the remaining models and additionally the constructed variable ΔT, used in other non-linear models analysed in the other studies. The best fit for those models was obtained for the mountain stations (R² from 0.67 to 0.75, RMSE from 2.7 to 4.4). The poorest estimation was obtained for the coastal stations (R² from 0.41 to 0.67, RMSE from 2.6 to 5.1). The paper does not indicate the best month in terms of the fitting, due to the high variation of results for the stations and the models.

scholarly journals Comparison of the parameters of the lactation curve between normal and difficult calvings in Iranian Holstein cows

2019 ◽  
Vol 17 (1) ◽  
pp. e0401
Author(s):  
Navid Ghavi Hossein-Zadeh
Keyword(s):  
Dairy Cows ◽  
Milk Yield ◽  
Goodness Of Fit ◽  
Linear Models ◽  
Information Criterion ◽  
Holstein Cows ◽  
Coefficient Of Determination ◽  
Lactation Curve ◽  
Non Linear ◽  
Best Fit

To evaluate effect of dystocia on the lactation curve characteristics for milk yield and composition in Holstein cows, six non-linear models (Brody, Wood, Sikka, Nelder, Dijkstra and Rook) were fitted on 5,917,677 test day records for milk yield (MY), fat (FP) and protein (PP) percentages, fat to protein ratio (FPR) and somatic cell score (SCS) of 643,625 first lactation Holstein cows with normal calving or dystocia from 3146 herds which were collected by the Animal Breeding Center of Iran. The models were tested for goodness of fit using adjusted coefficient of determination, root means square error, Akaike’s information criterion and Bayesian information criterion. Rook model provided the best fit of the lactation curve for MY and SCS in normal and difficult calvers and dairy cows with dystocia for FP. Dijkstra model provided the best fit of the lactation curve for PP and FPR in normal and difficult calvers and dairy cows with normal calving for FP. Dairy cows with dystocia had generally lower 100-d, 200-d and 305-d cumulative milk yield compared with normal calvers. Time to the peak milk yield was observed later for difficult calvers (89 days in milk vs. 79 days in milk) with lower peak milk yield (31.45 kg vs. 31.88 kg) compared with normal calvers. Evaluation of the different non-linear models indicated that dystocia had important negative effects on milk yield and lactation curve characteristics in dairy cows and it should be reduced as much as possible in dairy herds.

scholarly journals Growth curves for Ile de France female sheep raised in feedlot

2016 ◽  
Vol 37 (1) ◽  
pp. 303 ◽  
Author(s):  
Raphael Patrick Moreira ◽  
Victor Breno Pedrosa ◽  
Paula Roberta Falcão ◽  
Michelli De Fátima Sieklicki ◽  
Caroline Gomes Rocha ◽  
...  
Keyword(s):  
Weight Gain ◽  
Negative Correlation ◽  
Linear Models ◽  
Growth Curves ◽  
Daily Weight Gain ◽  
Coefficient Of Determination ◽  
Mean Square ◽  
Non Linear ◽  
Best Fit ◽  
Female Sheep

The objective of the present study was to analize the non-linear models that best fit the growth of ewes Ile de France. The experiment was conducted in school farm Capão da Onça, located in city of Ponta Grossa - PR and so, were used data on weight at birth to 210 days of age of 34 females of the breed Ile de France. The animals showed mean weight at birth (PN) of 4,58 kilograms, weaning weight (P60) of 19,58 kilograms and weight at 210 days (P210) equal to 43,18 kilograms, providing daily weight gain (GMD) equal to 0,183 kg/day. The non-linear models used were: Brody, Von Bentarlanffy, Logístic and Gompertz, presenting results, respectively, of 33.5453; 33.7120; 33.6714 and 33.8836 for Error Mean Square (EMS) and 0.9650; 0.8302; 0.9649 and 0.9647 for coefficient of determination (R2). All models tended to describe accordingly the curve of animals growth, but, according to the methods adopted to select the most appropriate model, Von Bertarlanffy showed the best fit. All models presented high and negative correlation between the A and k parameters, indicating that the most precocious animals are less likely to reach elevated weights for 210 days of age

Design Equations for Bod Removal in Facultative Ponds

1987 ◽  
Vol 19 (12) ◽  
pp. 187-193 ◽  
Author(s):  
E. Joe Middlebrooks
Keyword(s):  
Environmental Protection Agency ◽  
Linear Models ◽  
Plug Flow ◽  
Empirical Models ◽  
The Us ◽  
Non Linear ◽  
The Usa ◽  
Using Data ◽  
Removal Model ◽  
Best Fit

Facultative pond performance data collected for the US Environmental Protection Agency (USEPA) at four locations throughout the USA and data collected by others were used to evaluate the most frequently used design equations and to develop non-linear design equations. Empirical models were evaluated as well as the classical plug flow and complete mix models. The first order plug flow model gave the best fit of all the rational models. The empirical non-linear models did not fit the data, nor did the other empirical models with the exception being the areal loading and removal model. Attempts to verify the models developed with the USEPA data using data collected by others were not successful with the exception of the areal loading and removal model.

scholarly journals Estimation of annual compound growth rates of guava (Psidium guajava L.) fruit in Haryana using Non linear model

2019 ◽  
Vol 11 (4) ◽  
pp. 778-784
Author(s):  
Pardeep Panghal ◽  
Manoj Kumar ◽  
Sarita Rani
Keyword(s):  
Growth Rate ◽  
Linear Model ◽  
Growth Rates ◽  
Logistic Model ◽  
Linear Models ◽  
Psidium Guajava ◽  
Annual Growth Rate ◽  
Guava Fruit ◽  
Non Linear ◽  
Best Fit

Computation of growth rates plays an important role in agricultural and economic research to study growth pattern of a various commodities. Many of the research workers used the parametric approach for computation of annual growth rate but not use the concept of non-linear model.  In this paper, an attempt has been made to study growth rates of guava for three districts (Hisar, and Kurukshetra) and Haryana state as a whole using different non-linear models. The time series data on annual area and production of guava (Psidium guajava L.) in different districts of Haryana from 1990-91 to 2015-16 were collected to fit non linear models. Growth rates were computed through best fitted non-linear models. It was found that Logistic model could be best fit for computation of growth rates of area for guava fruit in Hisar and Kurukshetra district and Haryana state as a whole whereas Gompertz model was best fit for Yamunanagar district based on high R2 and least MSE and RMSE values. It was also observed that monomolecular model was best fit for production of guava fruits in Hisar and Yamunanagar district whereas Logistic model was best fit for production of guava fruit in Kurukshetra and Haryana state as a whole because of high R2 and least MSE and RMSE values. R and excel software have been used for fitting the non linear model and computation of growth rates for area and production of guava fruit for the year 1990-91 to 2015-16. None has been used the non linear model growth model for computation of annual growth rate of guava fruit for area and production of Haryana state. But in this work non linear growth model has been used for computation of growth rate instead of parametric approaches.

scholarly journals Evaluation of non-linear models to describe development and fertility of codling moth at constant temperatures

2017 ◽  
Vol 20 (1) ◽  
pp. 3 ◽  
Author(s):  
H. Ranjbar Aghdam ◽  
Y. Fathipour ◽  
D. C. Kontodimas
Keyword(s):  
Goodness Of Fit ◽  
Linear Models ◽  
Information Criterion ◽  
Developmental Rate ◽  
Codling Moth ◽  
Coefficient Of Determination ◽  
Temperature Threshold ◽  
Optimum Temperature ◽  
Non Linear ◽  
Lower Temperature

Developmental rate of immature stages and age-specific fertility of females of codling moth at constant temperatures was modeled using non-linear models. The equations of Enkegaard, Analytis, and Bieri 1 and 2 were evaluated based on the value of adjusted R2 (R2adj) and Akaike information criterion (AIC) besides coefficient of determination (R2) and residual sum of squares (RSS). All models have goodness of fit to data especially for development [R2, R2adj, RSS and AIC ranged 0.9673-0.9917, 0.8601-0.9861, 0.08-6.7x10-4 and (-75.29) – (-46.26) respectively]. Optimum temperature (Topt) and upper threshold (Tmax) were calculated accurately (Topt and Tmax ranged 29.9-31.2oC and 35.9-36.7oC) by all models. Lower temperature threshold (Tmin) was calculated accurately by Bieri-1 model (9,9-10,8oC) whereas Analytis model (7,0-8,4oC) underestimated it. As far as fertility is concerned the respective values were better fitted near the optimum temperature (in 30oC) [R2 ,R2adj, RSS and AIC ranged 0,6966-0,7744, 0,5756-0,6455, 2,44-3,33 x10-4 and (-9,15)-7,15 respectively].

scholarly journals Are African Stock Markets Inefficient or Adaptive? Empirical Literature

2020 ◽  
Author(s):  
Adefemi A. Obalade ◽  
Paul-Francois Muzindutsi
Keyword(s):  
Stock Returns ◽  
Stock Markets ◽  
Linear Models ◽  
Empirical Studies ◽  
Weak Form ◽  
Empirical Literature ◽  
Recent Theory ◽  
Non Linear ◽  
Best Fit ◽  
Weak Form Efficiency

This chapter reviews empirical studies on weak form of efficiency with the aim of establishing whether the African market is inefficient or adaptive. The reviewed studies are categorised based on their methodological approaches to compare the power of linear and non-linear models in testing for weak-form efficiency. The studies on calendar anomalies, an indication of weak-form inefficiency, are reviewed to assess whether these anomalies are adaptive as portrayed by the relatively recent theory of adaptive market hypothesis (AMH). The scope of reviewed studies is also extended to developed and emerging markets to gain a broad comparison of the findings. This review revealed that non-linear dependence has been revealed in stock returns suggesting that non-linear models are best fit to test for the stock market efficiency. Reviewed studies produced contradictory findings with some supporting and others rejecting weak-form efficiency. Thus, most studies support the AMH, which suggests that market efficiencies and anomalies are time changing. This chapter concludes that most of the existing studies on AMH have been carried out in markets other than Africa, and hence, further empirical studies on the evolving and changing nature of efficiency in African stock markets are recommended.

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

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.

scholarly journals Statistical relationship between date of sowing and the sorghum shootfly (Atherigona Soccata, Rondani L)

2015 ◽  
Vol 7 (1) ◽  
pp. 77-82
Author(s):  
S. T. Pavan Kumar ◽  
Y. N. Havaldar ◽  
Shekharappa Shekharappa ◽  
Adam Kamei
Keyword(s):  
Standard Error ◽  
Heart Development ◽  
Quadratic Model ◽  
Coefficient Of Determination ◽  
Linear Quadratic ◽  
Kharif Season ◽  
Shoot Fly ◽  
Non Linear ◽  
Cubic Model ◽  
Best Fit

The present study was based on the available data of eleven years for shoot fly from 2000-2010 for kharif season. Different models viz., linear and non linear were tried to fit, Amongst, the linear, quadratic and cubic models produced better coefficient of determination and the models viz., EGG(Shoot fly Egg) =3.760+0.196(DOS) (R2 =0.892) and EGG(Shoot fly Egg) =1.077+1.195(DOS)-0.087(DOS^2), which produced highest R2 (0.896 at p=0.05) with less standard error (0.419) and quadratic model was also the best fit model in determining the oviposition of shoot fly, which explained 89.6 per cent variation in the oviposition of shoot fly for the 7 days after emergence of the sorghum crop. For the dead heart development (14 DAE), the model %DH (% Dead Heart) =3.535+3.104(DOS) found best fit with highest coefficient of determination of 0. 856 and exhibited significant positive relationship with the date of sowing and during 21 DAE the cubic model %DH (% Dead Heart) =10.619+10.115(DOS)-3.466(DOS^2)+0 .321(DOS ^3) had significant coefficient of determination value of 0.988 with least standard error 0.885. The quadratic model during the 28 days after emergence of the crop %DH (% Dead Heart) =-6.234+22.858(DOS) -1.399 (DOS^2) found best fit and produced significant R2 (0.929 at 5 per cent level) and showed better relationship with the date of sowing. It was found that, both linear and non linear relationship exists between dates of sowing and shoot fly of sorghum during kharif season.

scholarly journals Temperature driven development of the rice brown planthopper, Nilaparvata lugens (Stål) (Hemiptera: Delphacidae)

2021 ◽  
Vol 21 (2) ◽  
pp. 131-140
Author(s):  
JHANSILAKSHMI VATTIKUTI ◽  
V. SAILAJA ◽  
Y.G. PRASAD ◽  
P.M.CHIRUTKAR ◽  
G. RAMACHANDRA RAO ◽  
...  
Keyword(s):  
Linear Models ◽  
Brown Planthopper ◽  
Nilaparvata Lugens ◽  
Coefficient Of Determination ◽  
Temperature Threshold ◽  
Life Stages ◽  
Thermal Constants ◽  
Non Linear ◽  
Nilaparvata Lugens Stål ◽  
Phenology Model

Temperature driven development of rice brown planthopper (BPH), Nilaparvata lugens (Stål) (Hemiptera: Delphacidae) population (biotype 4) was examined at seven constant temperatures (15, 18, 20, 25, 30, 32 and 35°C). Complete development of BPH from egg to adult was observed at constant temperatures ranging from 15 to 32°C with linear development observed till 30°C. Total immaturedevelopmental duration decreased from 74.4 days at 15°C to 22.4 days at 30°C. Linear and non-linear models fitted to describe developmental rates of life stages as a function of temperature, gave estimates of bioclimatic thresholds (lower, optimum and upper temperature thresholds). Thermal constants estimated from Campbell linear model for egg, nymph and cumulative immature development to adult were, 198.8, 275.5 and 473.9 degree days, respectively. Among empirical non-linear models, Lactin 2 model was selected for estimates of upper temperature threshold at 35°C based on higher coefficient of determination. Application of thermodynamic SSI model explained the observed nonlinear relationship of development of BPH life stages at temperatures higher than 30°C. The estimated thermal constants and bioclimatic thresholds were used in developing temperature dependent phenology model based on Campbell equation. Phenology model predicted closely the occurrence of different life stages of BPH with those observed under field conditions. 

scholarly journals Comparative study of some non-linear models for predicting the yield of Gmelina arborea plantation

2014 ◽  
Vol 6 (2) ◽  
pp. 738-743
Author(s):  
F. O. Oboite ◽  
V. D. Ade-Oni
Keyword(s):  
Linear Models ◽  
Logistic Models ◽  
Basal Area ◽  
Weibull Model ◽  
Volume Estimation ◽  
Coefficient Of Determination ◽  
Gmelina Arborea ◽  
Non Linear ◽  
The One ◽  
Log Normal

Yield models are important for effective forest management and as such were developed for the University of Benin Gmelina arborea plantation, Nigeria. The objectives of the study were to develop, evaluate and compare predictions from some non-linear models for timber volume estimation. A total of nine non-linear models comprising of three models each for weibull, logistic and log-normal models were developed using the three independent variables combinations (Basal area and merchantable height, diameter at base and merchantable height, diameter at middle and merchantable height). The assessment criteria (correlation coefficient (R), coefficient of determination (R2), standard error of estimate (SE)) with the validation results (using percentage bias and probability plots of residuals) showed that all categories of weibull and logistic models generated in this study discovered to be very adequate for tree volume estimation. The highest R2 (93.80), lowest SE (0.25) and lowest bias% (1.29) in the study were achieved from Weibull model 1a. The log-normal models were the least adequate for tree volume estimation with the highest bias%. The one way analysis of variance revealed that there were no significant differences in the performance of the non-linear models when varying predictor variables were used. The weibull, logistic models were therefore recommended for further use in this ecosystem and in any other forest ecosystem with similar site condition.

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