scholarly journals Variability in rainfall dispersion in Madhya Pradesh

MAUSAM ◽  
2021 ◽  
Vol 43 (1) ◽  
pp. 29-36
Author(s):  
H.P. DAS ◽  
A. CHOWDHURY
Keyword(s):  
Gamma Distribution ◽  
Rainfall Variability ◽  
Probability Model ◽  
Regional Distribution ◽  
Madhya Pradesh ◽  
Regression Equations ◽  
Scale Parameters ◽  
Agronomic Practices ◽  
Distribution Probability ◽  
The Mean

An attempt has been made to examine distribution and dispersion in rainfall variability in Madhya Pradesh by applying Gamma distribution probability model, The spatial and regional distribution of shape and scale parameters of the Gamma distribution have been examined, Periods of water surpluses and deficiencies have been identified by comparing the probability rainfall with the water requirement. Regression equations have been developed to find probabilitistic rainfall from the mean rainfall. Agronomic practices have been evaluated for efficient utilization of water resources for crop planning.  

scholarly journals Bayesian Estimation for Two Parameters of Gamma Distribution under Generalized Weighted Loss Function

2019 ◽  
Vol 60 (5) ◽  
pp. 1161-1171
Author(s):  
Loaiy F. Naji ◽  
Huda A. Rasheed
Keyword(s):  
Bayesian Estimation ◽  
Gamma Distribution ◽  
Loss Function ◽  
Maximum Likelihood Estimators ◽  
Simulation Method ◽  
Monte Carlo Simulation Method ◽  
Mean Squared Errors ◽  
Scale Parameters ◽  
The Mean ◽  
Two Parameters

This paper deals with, Bayesian estimation of the parameters of Gamma distribution under Generalized Weighted loss function, based on Gamma and Exponential priors for the shape and scale parameters, respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation. Based on Monte Carlo simulation method, those estimators are compared in terms of the mean squared errors (MSE’s).

scholarly journals Bayesian Estimation for Two Parameters of Gamma Distribution Under Precautionary Loss Function

2019 ◽  
Vol 32 (1) ◽  
pp. 193 ◽  
Author(s):  
Loaiy F. Naji ◽  
Huda Abdullah Rasheed
Keyword(s):  
Bayesian Estimation ◽  
Gamma Distribution ◽  
Loss Function ◽  
Simulation Method ◽  
Mean Squared Errors ◽  
Scale Parameters ◽  
Lindley’S Approximation ◽  
The Mean ◽  
Two Parameters ◽  
Better Than

In the current study, the researchers have been obtained Bayes estimators for the shape and scale parameters of Gamma distribution under the precautionary loss function, assuming the priors, represented by Gamma and Exponential priors for the shape and scale parameters respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation. Based on Monte Carlo simulation method, those estimators are compared depending on the mean squared errors (MSE’s). The results show that, the performance of Bayes estimator under precautionary loss function with Gamma and Exponential priors is better than other estimates in all cases.

Cadmium concentrations in kidneys of sheep and cattle in Western Australia. 1. Regional distribution

1994 ◽  
Vol 45 (4) ◽  
pp. 851 ◽  
Author(s):  
PW Morcombe ◽  
DS Petterson ◽  
HG Masters ◽  
PJ Ross ◽  
JR Edwards
Keyword(s):  
Western Australia ◽  
Geometric Mean ◽  
Regional Distribution ◽  
Adult Cattle ◽  
Agricultural Region ◽  
Wet Weight ◽  
The Mean ◽  
Winter Annual ◽  
Rate Of Accumulation ◽  
Cattle And Sheep

A sample of 4973 kidneys from sheep stratified by age and shire of origin within the Agricultural Region of Western Australia, was analysed for cadmium (Cd) content during the period August 1989 to April 1991. The geometric mean Cd concentration in the kidney of hogget ewes was 0.9 mg/kg, in 4-tooth ewes 1.47 mg/kg and in adult ewes 3.34 mg/kg on a wet weight basis. The mean Cd concentrations of either ewe or hogget flocks from different Divisions of the Agricultural Region did not differ from each other. The annual increase in Cd concentration of kidney from hogget sheep was estimated to be 0-65 mg/kg. The rate of accumulation of Cd in kidney from cattle and sheep grazing the same properties was similar. Kidneys from a sample of 354 adult cattle from the Kimberley Region and 483 aged sheep from the Pastoral Region, both areas of unimproved rangelands, had geometric mean Cd concentrations of 0.15 mg/kg and 0-31 mg/kg respectively. A higher Cd concentration in flocks from the divisions adjacent to the Agricultural Region may have resulted from the establishment of some volunteer species of winter annual pastures in the rangeland.

scholarly journals Statistical Downscaling of Daily Wind Speed Variations

2014 ◽  
Vol 53 (3) ◽  
pp. 660-675 ◽  
Author(s):  
Megan C. Kirchmeier ◽  
David J. Lorenz ◽  
Daniel J. Vimont
Keyword(s):  
Wind Speed ◽  
Gamma Distribution ◽  
Large Scale ◽  
Probabilistic Method ◽  
Probabilistic Approach ◽  
Local Scale ◽  
Scale Parameters ◽  
Wind Speeds ◽  
Distribution Shape ◽  
Realistic Information

AbstractThis study presents the development of a method to statistically downscale daily wind speed variations in an extended Great Lakes region. A probabilistic approach is used, predicting a daily-varying probability density function (PDF) of local-scale daily wind speed conditioned on large-scale daily wind speed predictors. Advantages of a probabilistic method are that it provides realistic information on the variance and extremes in addition to information on the mean, it allows the autocorrelation of downscaled realizations to be tuned to match the autocorrelation of local-scale observations, and it allows flexibility in the use of the final downscaled product. Much attention is given to fitting the proper functional form of the PDF by investigating the observed local-scale wind speed distribution (predictand) as a function of the decile of the large-scale wind (predictor). It is found that the local-scale standard deviation and the local-scale shape parameter (from a gamma distribution) are nonconstant functions of the large-scale predictor. As such, a vector generalized linear model is developed to relate the large-scale and local-scale wind speeds. Maximum likelihood and cross validation are used to fit local-scale gamma distribution shape and scale parameters to the large-scale wind speed. The result is a daily-varying probability distribution of local-scale wind speed, conditioned on the large-scale wind speed.

scholarly journals Using Empirical Orthogonal Teleconnections to evaluate interannual rainfall variability over China in the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations

2017 ◽  
Author(s):  
Claudia Christine Stephan ◽  
Nicholas P. Klingaman ◽  
Pier Luigi Vidale ◽  
Andrew G. Turner ◽  
Marie-Estelle Demory ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Rainfall Variability ◽  
Reanalysis Data ◽  
Horizontal Resolution ◽  
Unified Model ◽  
Seasonal Precipitation ◽  
Climate Simulations ◽  
Interannual Rainfall Variability ◽  
The Mean

Abstract. Six climate simulations of the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations are evaluated against observations and reanalysis data for their ability to simulate the mean state and year-to-year variability of precipitation over China. To analyze the sensitivity to air-sea coupling and horizontal resolution, atmosphere-only and coupled integrations at atmospheric horizontal resolutions of N96, N216 and N512 (corresponding to ~ 200, 90, and 40 km in the zonal direction at the equator, respectively) are analyzed. The mean and interannual variance of seasonal precipitation are too high in all simulations over China, but improve with finer resolution and coupling. Empirical Orthogonal Teleconnection (EOT) analysis is applied to simulated and observed precipitation to identify spatial patterns of temporally coherent interannual variability in seasonal precipitation. To connect these patterns to large-scale atmospheric and coupled air-sea processes, atmospheric and oceanic fields are regressed onto the corresponding seasonal-mean timeseries. All simulations reproduce the observed leading pattern of interannual rainfall variability in winter, spring and autumn; the leading pattern in summer is present in all but one simulation. However, only in two simulations are the four leading patterns associated with the observed physical mechanisms. Coupled simulations capture more observed patterns of variability and associate more of them with the correct physical mechanism, compared to atmosphere-only simulations at the same resolution. However, finer resolution does not improve the fidelity of these patterns or their associated mechanisms. This shows that evaluating climate models by only geographical distribution of mean precipitation and its interannual variance is insufficient. The EOT analysis adds knowledge about coherent variability and associated mechanisms.

scholarly journals Living mulch strategy for organic cauliflower (Brassica oleracea L.) production in central and southern Italy

2015 ◽  
Vol 10 (2) ◽  
pp. 90 ◽  
Author(s):  
Stefano Canali ◽  
Gabriele Campanelli ◽  
Corrado Ciaccia ◽  
Mariangela Diacono ◽  
Fabrizio Leteo ◽  
...  
Keyword(s):  
Brassica Oleracea ◽  
Field Experiments ◽  
Southern Italy ◽  
Central Italy ◽  
Climatic Conditions ◽  
F1 Hybrid ◽  
Agronomic Practices ◽  
Burr Medic ◽  
The Mean ◽  
Sustainable Agricultural Systems

In sustainable agricultural systems, intercropping using living mulches (LM) provides many beneficial ecosystem services. The objective of these two-year field experiments was to study the suitability of different LM options of burr medic (<em>Medicago polymorpha</em> L. var. <em>anglona</em>) for organic cauliflower (<em>Brassica oleracea</em> L.) cultivation in two sites under Mediterranean conditions. In central Italy (Experiment 1) contemporary and delayed (to crop) sowings of LM were compared with a no-cover crop treatment, contrasting two local cauliflower cultivars and a F1 Hybrid. In southern Italy (Experiment 2) the sustainability of systems combining LM (anticipated and contemporary sowing compared with no-cover) and organic fertilisation strategies was assessed. The aboveground biomasses dry weights of cauliflower crop (heads and residues), burr medic and weeds were separately determined. Results suggested that in Experiment 1 the LM was not able to smother weeds establishment and growth, as a consequence of early sowing, while cauliflower yield was reduced. Moreover, the genotypes behaviour was greatly influenced by the LM sowing times. In Experiment 2, irrespective of the agronomic practices applied, climatic conditions notably influenced cauliflower cultivation and also reduced the mean yield. Therefore, the recorded differences between the two experimental sites highlighted the need to tailor the LM strategies to the different environmental conditions.

scholarly journals Generalized predictive model of estimation of inhibition of muscarinic receptors M1-M5

2020 ◽  
Vol 3 (3) ◽  
pp. e00129
Author(s):  
A.V. Mikurova ◽  
V.S. Skvortsov ◽  
V.V. Grigoryev
Keyword(s):  
Predictive Model ◽  
Muscarinic Receptors ◽  
Three Dimensional ◽  
Dynamics Simulation ◽  
Dimensional Structure ◽  
Regression Equations ◽  
Energy Characteristics ◽  
Value Prediction ◽  
M3 Receptor ◽  
The Mean

A general predictive model for assessing the inhibition constant (K<sub>i</sub>) value of human acetylcholine muscarinic receptors M1-M5 by potential ligands has been constructed. We used information on the three-dimensional structure of human M1, M2, M4, and M5 receptors, as well as a model of the M3 receptor constructed according to homology based on the structure of the rat M3 receptor. A set of complexes of known inhibitors with the target receptor constructed by means of molecular docking, was selected using an additional option: the coincidence of the spatial position of 4 pharmacophore points of a tested inhibitor and tiotropium, for which the position in the crystal structure was known. For five types of M receptors 199 complexes with known K<sub>i</sub> values were selected. Based on the data obtained during molecular dynamics simulation of these complexes by means of the MM-PBSA/MM-GBSA methods, their energy characteristics were calculated. They were used as independent variables in linear regression equations for pK<sub>i</sub> value prediction. The R<sup>2</sup> prediction for the generalized equation was 0.7, and the mean prediction error was 0.55 logarithmic units with a range for pK<sub>i</sub>=4.7.

scholarly journals Prediksi Tinggi Badan Ditentukan dari Panjang Rentang Lengan dan Panjang Telapak Kaki Pada Mongoloid Feminina Khususnya Etnis Jawa

2018 ◽  
Vol 2 (2) ◽  
Author(s):  
Nur Mujaddidah Mochtar
Keyword(s):  
Clinical Medicine ◽  
Pearson Correlation ◽  
Body Height ◽  
Regression Equation ◽  
The Body ◽  
Regression Equations ◽  
Foot Length ◽  
Arm Span ◽  
Knee Height ◽  
The Mean

Background: There are various circumstances where measurements are not actually possible, replacement parameters can be used to estimate body height. Many characteristics of body height measurement and how to measure it. These include anthropometric measurements that can be used for the identification of medicolegal-forensic processes. Body height in clinical medicine and in the field of scientific research can be easily estimated using various anthropometric parameters such as arm span, knee height, foot length and foot breadth, and others. The arm span and foot length has proved to be one of the most reliable predictors. This study was conducted to estimate of body height from arm span and foot length using the regression equation and to determine the correlation between the body height and arm span and foot length.Methods: This study was conducted at Universitas Muhammadiyah Surabaya with 182 Javanese female students. Stature, arm span and foot length measured directly using anthropometric technique and measuring tape. The data obtained were then analyzed with SPSS version 16. The regression equation was derived for the estimate of body height and the relationship between stature, arm span and foot length determined by the Pearson correlation.               Results: We found that the mean body height of Javanese women was 1534,45 ± 47,623  mm, mean of arm span 1543,25 ± 60,468 mm and the mean of foot length 226,14 ± 9,586 mm. The correlation between stature and arm span was positive and significant (r = 0,715  , p <0,05). The correlation between stature and foot length was positive and significant (r = 0,726 , p <0,05). The correlation between stature and arm span and foot length was positive and significant (r = 0,798, p <0,05).               Conclusion: Body height correlates well with the arm span and foot length so that it can be used as a reliable marker for high estimates using regression equations.

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