Comparison Of Parameters Of Lognormal Distribution Based On The Classical And Posterior Estimates,
2013
University of Kashmir, Srinagar, India
Comparison Of Parameters Of Lognormal Distribution Based On The Classical And Posterior Estimates, Raja Sultan, S. P. Ahmad
Journal of Modern Applied Statistical Methods
Lognormal distribution is widely used in scientific field, such as agricultural, entomological, biology etc. If a variable can be thought as the multiplicative product of some positive independent random variables, then it could be modelled as lognormal. In this study, maximum likelihood estimates and posterior estimates of the parameters of lognormal distribution are obtained and using these estimates we calculate the point estimates of mean and variance for making comparisons.
On Bayesian Estimation And Predictions For Two-Component Mixture Of The Gompertz Distribution,
2013
Allama Iqbal Open University, Islamabad, Pakistan
On Bayesian Estimation And Predictions For Two-Component Mixture Of The Gompertz Distribution, Navid Feroze, Muhammad Aslam
Journal of Modern Applied Statistical Methods
Mixtures models have received sizeable attention from analysts in the recent years. Some work on Bayesian estimation of the parameters of mixture models have appeared. However, the were restricted to the Bayes point estimation The methodology for the Bayesian interval estimation of the parameters for said models is still to be explored. This paper proposes the posterior interval estimation (along with point estimation) for the parameters of a two-component mixture of the Gompertz distribution. The posterior predictive intervals are also derived and evaluated. Different informative and non-informative priors are assumed under a couple of loss functions for the posterior analysis. …
A Comparison Between Biased And Unbiased Estimators In Ordinary Least Squares Regression,
2013
King Khalid University, Saudi Arabia
A Comparison Between Biased And Unbiased Estimators In Ordinary Least Squares Regression, Ghadban Khalaf
Journal of Modern Applied Statistical Methods
During the past years, different kinds of estimators have been proposed as alternatives to the Ordinary Least Squares (OLS) estimator for the estimation of the regression coefficients in the presence of multicollinearity. In the general linear regression model, Y = Xβ + e, it is known that multicollinearity makes statistical inference difficult and may even seriously distort the inference. Ridge regression, as viewed here, defines a class of estimators of β indexed by a scalar parameter k. Two methods of specifying k are proposed and evaluated in terms of Mean Square Error (MSE) by …
Parameter Estimations Based On Kumaraswamy Progressive Type Ii Censored Data With Random Removals,
2013
Government Post Graduate College Muzaffarabad, Azad Kashmir, Pakistan
Parameter Estimations Based On Kumaraswamy Progressive Type Ii Censored Data With Random Removals, Navid Feroze, Ibrahim El-Batal
Journal of Modern Applied Statistical Methods
The estimation of two parameters of the Kumaraswamy distribution is considered under Type II progressive censoring with random removals, where the number of units removed at each failure time has a binomial distribution. The MLE was used to obtain the estimators of the unknown parameters, and the asymptotic variance - covariance matrix was also obtained. The formula to compute the expected test time was derived. A numerical study was carried out for different combinations of model parameters. Different censoring schemes were used for the estimation, and performance of these schemes was compared.
The Single-Case Data Analysis Package: Analysing Single-Case Experiments With R Software,
2013
KU Leuven, Belgium
The Single-Case Data Analysis Package: Analysing Single-Case Experiments With R Software, Isis Bulté, Patrick Onghena
Journal of Modern Applied Statistical Methods
The RcmdrPlugin.SCDA plug-in package is discussed. It integrates three R packages in the R commander interface: SCVA (for Single-Case Visual Analysis), SCRT (for Single-Case Randomization Tests), and SCMA (for Single-Case Meta-Analysis). This way the plug-in package covers three important steps in the analysis of single-case data.
Joint Estimation Of Multiple Graphical Models From High Dimensional Time Series,
2013
Johns Hopkins University
Joint Estimation Of Multiple Graphical Models From High Dimensional Time Series, Huitong Qiu, Fang Han, Han Liu, Brian Caffo
Johns Hopkins University, Dept. of Biostatistics Working Papers
In this manuscript the problem of jointly estimating multiple graphical models in high dimensions is considered. It is assumed that the data are collected from n subjects, each of which consists of m non-independent observations. The graphical models of subjects vary, but are assumed to change smoothly corresponding to a measure of the closeness between subjects. A kernel based method for jointly estimating all graphical models is proposed. Theoretically, under a double asymptotic framework, where both (m,n) and the dimension d can increase, the explicit rate of convergence in parameter estimation is provided, thus characterizing the strength one can borrow …
Combining Functions And The Closure Principle For Performing Follow-Up Tests In Functional Analysis Of Variance,
2013
University of Kentucky
Combining Functions And The Closure Principle For Performing Follow-Up Tests In Functional Analysis Of Variance, Olga A. Vsevolozhskaya, Mark C. Greenwood, G. J. Bellante, S. L. Powell, R. L. Lawrence, K. S. Repasky
Olga A. Vsevolozhskaya
Functional analysis of variance involves testing for differences in functional means across kk groups in nn functional responses. If a significant overall difference in the mean curves is detected, one may want to identify the location of these differences. Cox and Lee (2008) proposed performing a point-wise test and applying the Westfall–Young multiple comparison correction. We propose an alternative procedure for identifying regions of significant difference in the functional domain. Our procedure is based on a region-wise test and application of a combining function along with the closure multiplicity adjustment principle. We give an explicit formulation of how to implement …
Assessing Protein Conformational Sampling Methods Based On Bivariate Lag-Distributions Of Backbone Angles,
2013
Marquette University
Assessing Protein Conformational Sampling Methods Based On Bivariate Lag-Distributions Of Backbone Angles, Mehdi Maadooliat, Xin Gao, Jianhua Z. Huang
Mathematics, Statistics and Computer Science Faculty Research and Publications
Despite considerable progress in the past decades, protein structure prediction remains one of the major unsolved problems in computational biology. Angular-sampling-based methods have been extensively studied recently due to their ability to capture the continuous conformational space of protein structures. The literature has focused on using a variety of parametric models of the sequential dependencies between angle pairs along the protein chains. In this article, we present a thorough review of angular-sampling-based methods by assessing three main questions: What is the best distribution type to model the protein angles? What is a reasonable number of components in a mixture model …
Observed Versus Gcm-Generated Local Tropical Cyclone Frequency: Comparisons Using A Spatial Lattice,
2013
Embry-Riddle Aeronautical University
Observed Versus Gcm-Generated Local Tropical Cyclone Frequency: Comparisons Using A Spatial Lattice, Sarah Strazzo, Daniel J. Halperin, James Elsner, Tim Larow, Ming Zhao
Publications
Of broad scientific and public interest is the reliability of global climate models (GCMs) to simulate future regional and local tropical cyclone (TC) occurrences. Atmospheric GCMs are now able to generate vortices resembling actual TCs, but questions remain about their fidelity to observed TCs. Here the authors demonstrate a spatial lattice approach for comparing actual with simulated TC occurrences regionally using observed TCs from the International Best Track Archive for Climate Stewardship (IBTrACS) dataset and GCM-generated TCs from the Geophysical Fluid Dynamics Laboratory (GFDL) High Resolution Atmospheric Model (HiRAM) and Florida State University (FSU) Center for Ocean–Atmospheric Prediction Studies (COAPS) …
Innovationspotenzialanalyse Für Die Neuen Technologien Für Das Verwalten Und Analysieren Von Großen Datenmengen (Big Data Management),
2013
Santa Clara University
Innovationspotenzialanalyse Für Die Neuen Technologien Für Das Verwalten Und Analysieren Von Großen Datenmengen (Big Data Management), Volker Markl, Alexander Löser, Thomas Hoeren, Helmut Krcmar, Holmer Hemsen, Michael Schermann, Matthias Gottlieb, Christoph Buchmüller, Philip Uecker, Till Bitter
Faculty Book Gallery
Durch die Digitalisierung von Wirtschaft und Gesellschaft ist ein rasantes Anwachsen von Datenbeständen zu beobachten. In fast allen Unternehmenssowie Wissenschaftsbereichen werden bereits heute schon Unmengen an Daten erzeugt, deren Größe, Erfassungsgeschwindigkeit oder Heterogenität die Fähigkeiten gängiger Datenbanksoftwareprodukte zur Verwaltung und zur Analyse übersteigt. Dieses Phänomen, welches unter dem Schlagwort „Big Data“ popularisiert wurde, stellt eine große Chance für Unternehmen, Wissenschaft und Gesellschaft dar. Allerdings ergibt sich aufgrund der neuen Komplexität der Daten und Analysen eine Vielzahl an Herausforderungen technischer, wirtschaftlicher und rechtlicher Natur. Diese Studie analysiert die Chancen und Herausforderungen von Big Data insbesondere im Hinblick auf eine nachhaltige Wettbewerbsfä- …
Robust Regression Estimators When There Are Tied Values,
2013
University of Southern California, Los Angeles
Robust Regression Estimators When There Are Tied Values, Rand R. Wilcox, Florence Clark
Journal of Modern Applied Statistical Methods
It is well known that when using the ordinary least squares regression estimator, outliers among the dependent variable can result in relatively poor power. Many robust regression estimators have been derived that address this problem, but the bulk of the results assume that the dependent variable is continuous. It is demonstrated that when there are tied values, several robust regression estimators can perform poorly in terms of controlling the Type I error probability, even with a large sample size. The presence of tied values does not necessarily mean that they perform poorly, but there is the issue of whether there …
A Generalized Class Of Estimators For Finite Population Variance In Presence Of Measurement Errors,
2013
Banaras Hindu University, Varanasi, India
A Generalized Class Of Estimators For Finite Population Variance In Presence Of Measurement Errors, Prayas Sharma, Rajesh Singh
Journal of Modern Applied Statistical Methods
The problem of estimating the population variance is presented using auxiliary information in the presence of measurement errors. The estimators in this article use auxiliary information to improve efficiency and assume that measurement error is present both in study and auxiliary variable. A numerical study is carried out to compare the performance of the proposed estimator with other estimators and the variance per unit estimator in the presence of measurement errors.
Comparison Of Three Calculation Methods For A Bayesian Inference Of P(Π1 > Π2),
2013
National Center for Global Health and Medicine, Tokyo, Japan
Comparison Of Three Calculation Methods For A Bayesian Inference Of P(Π1 > Π2), Yohei Kawasaki, Asanao Shimokawa, Etsuo Miyaoka
Journal of Modern Applied Statistical Methods
In Bayesian inference, some researchers have examined the difference of binominal proportions using θ = P(π1 > π2 − Δ0|X1,X2), where Xi denote binomial random variable with parameter πi. An approximate method and the MCMC method are compared with an exact method for θ, and results of actual clinical trials using θ are presented.
Testing The Assumption Of Non-Differential Misclassification In Case-Control Studies,
2013
Western Illinois University, Macomb, IL
Testing The Assumption Of Non-Differential Misclassification In Case-Control Studies, Tze-San Lee, Qin Hui
Journal of Modern Applied Statistical Methods
One of the not yet solved issues regarding the misclassification in case-control studies is whether the misclassification rates are the same for both cases and controls. Currently, a common practice is to assume that the rates are the same, that is, the non-differential misclassification assumption. However, it has been suspected that this assumption may not be valid in practical applications. Unfortunately, no test is available so far to test the validity of the non-differential misclassification assumption. A method is presented to test the validity of non-differential misclassification assumption in case-control studies with 2 × 2 tables when validation data are …
Akaike Information Criterion To Select The Parametric Detection Function For Kernel Estimator Using Line Transect Data,
2013
King Abdulaziz University, Jeddah, Saudi Arabia
Akaike Information Criterion To Select The Parametric Detection Function For Kernel Estimator Using Line Transect Data, Omar Eidous, Samar Al-Salman
Journal of Modern Applied Statistical Methods
Among different candidate parametric detection functions, it is suggested to use Akaike Information Criterion (AIC) to select the most appropriate one of them to fit line transect data. Four different detection functions are considered in this paper. Two of them are taken to satisfy the shoulder condition assumption and the other two estimators do not satisfy this condition. Once the appropriate detection function is determined, it also can be used to select the smoothing parameter of the nonparametric kernel estimator. For a wide range of target densities, a simulation results show the reasonable and good performances of the …
Bayesian Joinpoint Regression Model For Childhood Brain Cancer Mortality,
2013
University of South Florida, Tampa, FL
Bayesian Joinpoint Regression Model For Childhood Brain Cancer Mortality, Ram C. Kafle, Netra Khanal, Chris P. Tsokos
Journal of Modern Applied Statistical Methods
The Bayesian approach of joinpoint regression is widely used to analyze trends in cancer mortality, incidence and survival data. The Bayesian joinpoint regression model was used to study the childhood brain cancer mortality rate and its average percentage change (APC) per year. Annual observed mortality counts of children ages 0-19 from 1969-2009 obtained from Surveillance Epidemiology and End Results (SEER) database of National Cancer Institute (NCI) were analyzed. It was assumed that death counts are probabilistically characterized by the Poisson distribution and they were modeled using log link function. Results were compared with the mortality trend obtained using joinpoint software …
Ordered Logit Regression Modeling Of The Self-Rated Health In Hawai‘I, With Comparisons To The Ols Model,
2013
University of South Alabama, Mobile, AL
Ordered Logit Regression Modeling Of The Self-Rated Health In Hawai‘I, With Comparisons To The Ols Model, Hosik Min
Journal of Modern Applied Statistical Methods
Despite the ordinal nature of Self-Rated Health (SRH) variable, logistic regression models or regression models have been used without adequate justification for these applications. It is shown that ordered-logit regression model is the appropriate statistical strategy to estimate SRH, whereas the Ordinary LeastSquares model leads to biased conclusions.
On Comparison Of Exponential And Hyperbolic Exponential Growth Models In Height/Diameter Increment Of Pines (Pinus Caribaea),
2013
University of Ibadan, Ibdan, Nigeria
On Comparison Of Exponential And Hyperbolic Exponential Growth Models In Height/Diameter Increment Of Pines (Pinus Caribaea), S. O. Oyamakin, A. U. Chukwu, T. A. Bamiduro
Journal of Modern Applied Statistical Methods
A new tree growth model called the hyperbolic exponential nonlinear growth model is suggested. Its ability in model prediction was compared with the Malthus or exponential growth model an approach which mimicked the natural variability of heights/diameter increment with respect to age and therefore provides more realistic height/diameter predictions as demonstrated by the results of the Kolmogorov Smirnov test and Shapiro-Wilk test. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the Hyperbolic exponential nonlinear growth models better than the ordinary exponential growth model without violating …
Approximation Multivariate Distribution Of Main Indices Of Tehran Stock Exchange With Pair-Copula,
2013
Shahid Chamran University, Ahvaz, Iran
Approximation Multivariate Distribution Of Main Indices Of Tehran Stock Exchange With Pair-Copula, G. Parham, A. Daneshkhah, O. Chatrabgoun
Journal of Modern Applied Statistical Methods
The multivariate distribution of five main indices of Tehran stock exchange is approximated using a pair-copula model. A vine graphical model is used to produce an n-dimensional copula. This is accomplished using a flexible copula called a minimum information (MI) copula as a part of pair-copula construction. Obtained results show that the achieved model has a good level of approximation.
On Some Properties Of A Heterogeneous Transfer Function Involving Symmetric Saturated Linear (Satlins) With Hyperbolic Tangent (Tanh) Transfer Functions,
2013
University of Ibadan, Ibadan, Nigeria
On Some Properties Of A Heterogeneous Transfer Function Involving Symmetric Saturated Linear (Satlins) With Hyperbolic Tangent (Tanh) Transfer Functions, Christopher Godwin Udomboso
Journal of Modern Applied Statistical Methods
For transfer functions to map the input layer of the statistical neural network model to the output layer perfectly, they must lie within bounds that characterize probability distributions. The heterogeneous transfer function, SATLINS_TANH, is established as a Probability Distribution Function (p.d.f), and its mean and variance are shown.
