Simultaneous inferences for ordered exponential location parameters under unbalanced data and heteroscedasticity of scale parameters

2016 ◽  
Vol 46 (4) ◽  
pp. 3129-3139
Author(s):  
A. N. Gill ◽  
Anju Goyal ◽  
Vishal Maurya
Keyword(s):  
Unbalanced Data ◽  
Scale Parameters ◽  
Location Parameters ◽  
Simultaneous Inferences

Analyzing treatment effects on Douglas-fir seedling survival with an extreme value regression model

1987 ◽  
Vol 17 (12) ◽  
pp. 1627-1630 ◽  
Author(s):  
Douglas A. Maguire ◽  
Christine C. Maguire
Keyword(s):  
Regression Model ◽  
Seedling Survival ◽  
Extreme Value ◽  
Douglas Fir ◽  
First Year ◽  
Scale Parameters ◽  
Location Parameters ◽  
Indicator Variables ◽  
Regression Approach ◽  
Survival Patterns

First year survival patterns in a cohort of natural Douglas-fir (Pseudotsugamenziesii (Mirb.) Franco) seedlings were assessed with an extreme value regression model. Extreme value distributions were fit to the data, assuming equal scale parameters among treatments but allowing location parameters to vary. The regression approach using indicator variables facilitated statistical comparison of survival curves among several habitats and treatments.

scholarly journals IDENTIFICATION OF RAINFALL DISTRIBUTION IN WEST SUMATERA AND ASSESSMENT OF ITS PARAMETERS USING BAYES METHOD

2020 ◽  
Vol 13 (2) ◽  
pp. 161-169
Author(s):  
Ferra Yanuar ◽  
Putri Trisna Sari ◽  
Yudiantri Asdi
Keyword(s):  
Direct Method ◽  
Likelihood Estimation ◽  
Rainfall Data ◽  
Bayes Method ◽  
Scale Parameters ◽  
Direct Estimation ◽  
Location Parameters ◽  
West Sumatra ◽  
Mean And Variance ◽  
The Mean

One distribution of rainfall data is a lognormal distribution with location parameters  and scale parameters . This study aims to estimate the mean and variance of rainfall data in several selected cities and regencies in West Sumatra. Parameter estimation is estimated by using maximum likelihood estimation (direct method) and Bayes method. This study resulted that the Bayes method produces a better predictive value with a smaller variance value than with direct estimation. It was concluded that the estimation by the Bayes method was a better estimator method than the direct estimation.

scholarly journals Predicting fruit and vegetable processing wash-water quality

2018 ◽  
Vol 2017 (1) ◽  
pp. 256-269 ◽  
Author(s):  
Gurvinder S. Mundi ◽  
Richard G. Zytner ◽  
Keith Warriner ◽  
Bahram Gharabaghi
Keyword(s):  
Water Quality ◽  
Oxygen Demand ◽  
Quality Parameters ◽  
Wash Water ◽  
Fruit And Vegetable ◽  
Adequate Treatment ◽  
Scale Parameters ◽  
Regulatory Standards ◽  
Location Parameters ◽  
Function Models

Abstract Wastewaters from the fresh produce processing industry are high in solids and organic matter requiring adequate treatment prior to disposal or recycling. Characterization of the processing wastewater, also referred to as wash-water is challenging, as the quality is a function of the produce. Analysis of water quality parameters, such as total suspended solids, total solids, total dissolved solids, chemical oxygen demand, biochemical oxygen demand, total nitrogen, total phosphorus, ammonia, and electrical conductivity from different fruit and vegetable operations were analyzed to develop the innovative power function models and ranking system to estimate wash-water quality. The developed models take the form of Y = a(x)b, where Y, a, x, and b are estimate, scale, rank, and location parameters, respectively. The location and rank range from −0.65 to −3.18 and 0.05 (worst water quality) to 1, respectively, while the scale parameters are highly variable. Average and standard deviation estimation models show a very good fit for washing only (R2 > 73%) and washing with processing (R2 > 79%). The models and ranks highlight the degree of treatment required to address protection of surface and ground water and make the water quality conform to regulatory standards, benefiting watershed managers, government agencies, consultants, farmers, producers, processors and technology providers.

scholarly journals Research on Selection Method of Privacy Parameter ε

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Pan Jun Sun
Keyword(s):  
Fault Tolerance ◽  
Privacy Protection ◽  
Differential Privacy ◽  
Success Probability ◽  
Tolerance Interval ◽  
Simulation Experiments ◽  
Scale Parameters ◽  
Location Parameters ◽  
Parameter Configuration ◽  
Selection Of

Budget factor is an important factor to measure the intensity of differential privacy, and its allocation scheme has a great impact on privacy protection. This paper studies the selection of the parameter ε in several cases of differential privacy. Firstly, this paper proposes a differential privacy protection parameter configuration method based on fault tolerance interval and analyzes the adversaryʼs fault tolerance under different noise distribution location parameters and scale parameters. Secondly, this paper proposes an algorithm to optimize the application scenarios of multiquery, studies the location parameters and scale parameters in detail, and proposes a differential privacy mechanism to solve the multiuser query scenarios. Thirdly, this paper proposes the differential privacy parameter selection methods based on the single attack and repeated attacks and calculates the upper bound of the parameter ε based on the sensitivity Δ q , the length of the fault tolerance interval L , and the success probability p as long as the fault tolerance interval. Finally, we have carried out a variety of simulation experiments to verify our research scheme and give the corresponding analysis results.

scholarly journals Efficient reliability estimation in two-parameter exponential distributions

Filomat ◽  
2018 ◽  
Vol 32 (4) ◽  
pp. 1455-1463 ◽  
Author(s):  
M. Mahdizadeh ◽  
Ehsan Zamanzade
Keyword(s):  
Unbiased Estimator ◽  
Minimum Variance ◽  
Reliability Estimation ◽  
Exponential Distributions ◽  
Minimum Variance Unbiased Estimator ◽  
Scale Parameters ◽  
Highly Efficient ◽  
Location Parameters ◽  
Simulation Results ◽  
Two Parameter

This article concerns reliability estimation in two-parameter exponential distributions setup with known scale parameters, and unknown location parameters. Based on the uniformly minimum variance unbiased estimator, we propose a new estimator and study its theoretical properties. Simulation results reveal that the suggested estimator could be highly efficient.

Modeling Self-Determination Theory Motivation Data by Using Unfolding IRT

2020 ◽  
pp. 1-9
Author(s):  
Philipp A. Freund ◽  
Annette Lohbeck
Keyword(s):  
Ideal Point ◽  
Self Determination Theory ◽  
Self Determination ◽  
Dominance Model ◽  
Irt Model ◽  
Autonomous Behavior ◽  
Location Parameters ◽  
Unfolding Models ◽  
Using Data ◽  
Item Location

Abstract. Self-determination theory (SDT) suggests that the degree of autonomous behavior regulation is a characteristic of distinct motivation types which thus can be ordered on the so-called Autonomy-Control Continuum (ACC). The present study employs an item response theory (IRT) model under the ideal point response/unfolding paradigm in order to model the response process to SDT motivation items in theoretical accordance with the ACC. Using data from two independent student samples (measuring SDT motivation for the academic subjects of Mathematics and German as a native language), it was found that an unfolding model exhibited a relatively better fit compared to a dominance model. The item location parameters under the unfolding paradigm showed clusters of items representing the different regulation types on the ACC to be (almost perfectly) empirically separable, as suggested by SDT. Besides theoretical implications, perspectives for the application of ideal point response/unfolding models in the development of measures for non-cognitive constructs are addressed.

Sign in / Sign up

Export Citation Format

Share Document