JournalTOCs

Journal of Modern Applied Statistical Methods
Journal Prestige (SJR): 0.298

Number of Followers: 1

This is an Open Access Journal

Open Access journal
ISSN (Print) 1538-9472
Published by Wayne State University

[3 journals]

Two Sample Statistical Test for Location Parameters
- Authors: Narinder Kumar et al.
  Abstract: A class of distribution-free tests for the homogeneity of location parameters is proposed and compared with different competitors in terms of Pitman asymptotic relative efficiency. A numerical example is provided and a simulation study is made to check the performance of the tests.
  PubDate: Mon, 24 Apr 2023 13:48:28 PDT
Parametric and Reliability Estimation of the Kumaraswamy Generalized
Distribution Based on Record Values
- Authors: Mohd. Arshad et al.
  Abstract: A general family of distributions, namely Kumaraswamy generalized family of (Kw-G) distribution, is considered for estimation of the unknown parameters and reliability function based on record data from Kw-G distribution. The maximum likelihood estimators (MLEs) are derived for unknown parameters and reliability function, along with its confidence intervals. A Bayesian study is carried out under symmetric and asymmetric loss functions in order to find the Bayes estimators for unknown parameters and reliability function. Future record values are predicted using Bayesian approach and non Bayesian approach, based on numerical examples and a monte carlo simulation.
  PubDate: Thu, 13 Jan 2022 12:35:33 PST
Does the Type of Records Affect the Estimates of the Parameters'
- Authors: Ayush Tripathi et al.
  Abstract: The maximum likelihood estimation of the unknown parameters of inverse Rayleigh and exponential distributions are discussed based on lower and upper records. The aim is to study the effect of the type of records on the behavior of the corresponding estimators. Mean squared errors are calculated through simulation to study the behavior of the estimators. The results shall be of interest to those situations where the data can be obtained in the form of either of the two types of records and the experimenter must decide between these two for estimation of the unknown parameters of the distribution.
  PubDate: Tue, 11 Jan 2022 06:35:18 PST
Design of SkSP-R Plan for Popular Statistical Distributions
- Authors: Jaffer Hussain et al.
  Abstract: The design of a Skip-lot sampling plan of type SkSP-R is presented for time truncated life test for the Weibull, Exponentiated Weibull, and Birnbaum-Saunders lifetime distributions. The plan parameters of the SkSP-R plan under these three distributions are determined through a nonlinear optimization problem. Tables are also constructed for each distribution. The advantages of the proposed plan over the existing sampling schemes are discussed. Application of the proposed plan is explained with the help of an example. The Birnbaum-Saunders distribution is economically superior to other two distributions in terms of minimum average sample number.
  PubDate: Fri, 07 Jan 2022 07:44:23 PST
Parameter Estimation Based on Double Ranked Set Samples with Applications
to Weibull Distribution
- Authors: Mohamed Abd Elhamed Sabry et al.
  Abstract: In this paper, the likelihood function for parameter estimation based on double ranked set sampling (DRSS) schemes is introduced. The proposed likelihood function is used for the estimation of the Weibull distribution parameters. The maximum likelihood estimators (MLEs) are investigated and compared to the corresponding ones based on simple random sampling (SRS) and ranked set sampling (RSS) schemes. A Monte Carlo simulation is conducted and the absolute relative biases, mean square errors, and efficiencies are compared for the different schemes. It is found that, the MLEs based on DRSS is more efficient than MLE using SRS and RSS for estimating the two parameters of the Weibull distribution (WD).
  PubDate: Thu, 06 Jan 2022 09:43:52 PST
A New Goodness of Fit Measure Based on Income Inequality Curves
- Authors: Shahryar Mirzaei et al.
  Abstract: This paper uses inequality-measurement techniques to assess goodness of fit in income distribution models. It exposes the shortcomings of the use of conventional goodness of fit criteria in face of the big income data and proposes a new set of metrics, based on income inequality curves. In this note, we mentioned that the distance between theoretical and empirical inequality curves can be considered as a goodness of fit criterion. We demonstrate certain advantages of this measure over the other general goodness of fit criteria. Unlike other goodness of fit measures, this criterion is bounded. It is 0 in minimum difference and 1 in maximum distance. Furthermore, there is a consistency between this new goodness of fit measure and the other conventional criteria. A simulation study based on fitted distribution to real income data is performed in order to investigate some statistical properties of the new goodness of fit measure. An empirical study and comparisons are also provided.
  PubDate: Mon, 03 Jan 2022 13:01:52 PST
Non-Parametric Tests for Testing of Scale Parameters
- Authors: Manish Goyal et al.
  Abstract: One of the fundamental problems in testing of equality of populations is of testing the equality of scale parameters. The subsequent usages for scale are dispersion, spread and variability. In this paper, we proposed non-parametric tests based on U-Statistics for the testing of equality of scale parameters. The null distribution of proposed tests is developed and its Pitman efficiency is worked out to compare proposed tests with respect to some existing tests. Simulation study is carried out to compute the asymptotic power of proposed tests. An illustrative example is also provided.
  PubDate: Tue, 07 Dec 2021 12:22:26 PST
Comparative Study of New and Traditional Estimators of a New Lifetime
Model
- Authors: Sandeep Kumar Maurya et al.
  Abstract: In this article, we have studied the behavior of estimators of parameter of a new lifetime model, suggested by Maurya et al. (2016), obtained by using methods of moments, maximum likelihood, maximum product spacing, least squares, weighted least squares, percentile, Cramer-von-Mises, Anderson-Darling and Right-tailed Anderson-Darling. Comparison of the estimators has been done on the basis of their mean square errors, biases, absolute and maximum absolute differences between empirical and estimated distribution function and a newly proposed criterion. We have also obtained the asymptomatic confidence interval and associated coverage probability for the parameter.
  PubDate: Tue, 02 Nov 2021 08:19:26 PDT
On the Extension of Exponentiated Pareto Distribution
- Authors: Amal S. Hassan et al.
  Abstract: In this study, an extended exponentiated Pareto distribution is proposed. Some statistical properties are derived. We consider maximum likelihood, least squares, weighted least squares and Bayesian estimators. A simulation study is implemented for investigating the accuracy of different estimators. An application of the proposed distribution to a real data is presented.
  PubDate: Fri, 08 Oct 2021 11:03:35 PDT
A New Generating Family of Distributions: Properties and Applications to
the Weibull Exponential Model
- Authors: El-Sayed A. El-Sherpieny et al.
  Abstract: A new method for generating family of distributions was proposed. Some fundamental properties of the new proposed family include the quantile, survival function, hazard rate function, reversed hazard and cumulative hazard rate functions are provided. This family contains several new models as sub models, such as the Weibull exponential model which was defined and discussed its properties. The maximum likelihood method of estimation is using to estimate the model parameters of the new proposed family. The flexibility and the importance of the Weibull-exponential model is assessed by applying it to a real data set and comparing it with other known models.
  PubDate: Wed, 29 Sep 2021 11:55:22 PDT
JMASM 55: MATLAB Algorithms and Source Codes of 'cbnet' Function
for Univariate Time Series Modeling with Neural Networks (MATLAB)
- Authors: Cagatay Bal et al.
  Abstract: Artificial Neural Networks (ANN) can be designed as a nonparametric tool for time series modeling. MATLAB serves as a powerful environment for ANN modeling. Although Neural Network Time Series Tool (ntstool) is useful for modeling time series, more detailed functions could be more useful in order to get more detailed and comprehensive analysis results. For these purposes, cbnet function with properties such as input lag generator, step-ahead forecaster, trial-error based network selection strategy, alternative network selection with various performance measure and global repetition feature to obtain more alternative network has been developed, and MATLAB algorithms and source codes has been introduced. A detailed comparison with the ntstool is carried out, showing that the cbnet function covers the shortcomings of ntstool.
  PubDate: Tue, 28 Sep 2021 10:45:31 PDT
Bayesian Sensitivity-Specificity and ROC Analysis for Finding Key Drivers
- Authors: Stan Lipovetsky et al.
  Abstract: Finding key drivers in regression modeling via Bayesian Sensitivity-Specificity and Receiver Operating Characteristic is suggested, and clearly interpretable results are obtained. Numerical comparisons with other techniques show that this methodology can be useful in practical statistical modeling and analysis helping to researchers and managers in making meaningful decisions.
  PubDate: Tue, 31 Aug 2021 11:52:54 PDT
Performance of the Beta-Binomial Model for Clustered Binary Responses:
Comparison with Generalized Estimating Equations
- Authors: Seongah Im
  Abstract: This study examined performance of the beta-binomial model in comparison with GEE using clustered binary responses resulting in non-normal outcomes. Monte Carlo simulations were performed under varying intracluster correlations and sample sizes. The results showed that the beta-binomial model performed better for small sample, while GEE performed well under large sample.
  PubDate: Mon, 16 Aug 2021 12:05:13 PDT
Pareto Distribution under Hybrid Censoring: Some Estimation
- Authors: Gyan Prakash
  Abstract: In the present study, the Pareto model is considered as the model from which observations are to be estimated using a Bayesian approach. Properties of the Bayes estimators for the unknown parameters have studied by using different asymmetric loss functions on hybrid censoring pattern and their risks have compared. The properties of maximum likelihood estimation and approximate confidence length have also been investigated under hybrid censoring. The performances of the procedures are illustrated based on simulated data obtained under the Metropolis-Hastings algorithm and a real data set.
  PubDate: Wed, 30 Jun 2021 06:56:26 PDT
Calibration-Based Estimators using Different Distance Measures under Two
Auxiliary Variables: A Comparative Study
- Authors: Piyush Kant Rai et al.
  Abstract: This article introduces calibration estimators under different distance measures based on two auxiliary variables in stratified sampling. The theory of the calibration estimator is presented. The calibrated weights based on different distance functions are also derived. A simulation study has been carried out to judge the performance of the proposed estimators based on the minimum relative root mean squared error criterion. A real-life data set is also used to confirm the supremacy of the proposed method.
  PubDate: Wed, 30 Jun 2021 06:56:16 PDT
Robust Lag Weighted Lasso for Time Series Model
- Authors: Tahir R. Dikheel et al.
  Abstract: The lag-weighted lasso was introduced to deal with lag effects when identifying the true model in time series. This method depends on weights to reflect both the coefficient size and the lag effects. However, the lag weighted lasso is not robust. To overcome this problem, we propose robust lag weighted lasso methods. Both the simulation study and the real data example show that the proposed methods outperform the other existing methods.
  PubDate: Thu, 17 Jun 2021 07:05:48 PDT
Inference for Step-Stress Partially Accelerated Life Test Model with an
Adaptive Type-I Progressively Hybrid Censored Data
- Authors: Showkat Ahmad Lone et al.
  Abstract: Consider estimating data of failure times under step-stress partially accelerated life tests based on adaptive Type-I hybrid censoring. The mathematical model related to the lifetime of the test units is assumed to follow Rayleigh distribution. The point and interval maximum-likelihood estimations are obtained for distribution parameter and tampering coefficient. Also, the work is conducted under a traditional Type-I hybrid censoring plan (scheme). A Monte Carlo simulation algorithm is used to evaluate and compare the performances of the estimators of the tempering coefficient and model parameters under both progressively hybrid censoring plans. The comparison is carried out on the basis of mean squared errors and bias.
  PubDate: Tue, 08 Jun 2021 09:14:57 PDT
JMASM 57: Bayesian Survival Analysis of Lomax Family Models with Stan (R)
- Authors: Mohammed H. A. Abujarad et al.
  Abstract: An attempt is made to fit three distributions, the Lomax, exponential Lomax, and Weibull Lomax to implement Bayesian methods to analyze Myeloma patients using Stan. This model is applied to a real survival censored data so that all the concepts and computations will be around the same data. A code was developed and improved to implement censored mechanism throughout using rstan. Furthermore, parallel simulation tools are also implemented with an extensive use of rstan.
  PubDate: Tue, 08 Jun 2021 07:53:46 PDT
Extending Singh-Maddala Distribution
- Authors: Mohamed Ali Ahmed
  Abstract: A new distribution, the exponentiated transmuted Singh-Maddala distribution (ETSM), is presented, and three important special distributions are illustrated. Some mathematical properties are obtained, and parameters estimation method is applied using maximum likelihood. Illustrations based on random numbers and a real data set are given.
  PubDate: Tue, 08 Jun 2021 07:53:38 PDT
A Simple Random Sampling Modified Dual to Product Estimator for estimating
Population Mean Using Order Statistics
- Authors: Sanjay Kumar et al.
  Abstract: Bandopadhyaya (1980) developed a dual to product estimator using robust modified maximum likelihood estimators (MMLE’s). Their properties were obtained theoretically and supported through simulations studies with generated as well as one real data set. Robustness properties in the presence of outliers and confidence intervals were studied.
  PubDate: Tue, 08 Jun 2021 07:53:30 PDT