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A comparison study on a new five-parameter generalized Lindley distribution with its sub-models

100%
Tharshan R., Wijekoon P.
Statistics in Transition new series
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2020
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vol. 21
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issue 2
89-117
EN
In recent years, modifications of the classical Lindley distribution have been considered by many authors. In this paper, we introduce a new generalization of the Lindley distribution based on a mixture of exponential and gamma distributions with different mixing proportions and compare its performance with its sub-models. The new distribution accommodates the classical Lindley, Quasi Lindley, Two-parameter Lindley, Shanker, Lindley distribution with location parameter, and Three-parameter Lindley distributions as special cases. Various structural properties of the new distribution are discussed and the size-biased and the lengthbiased are derived. A simulation study is conducted to examine the mean square error for the parameters by means of the method of maximum likelihood. Finally, simulation studies and some real-world data sets are used to illustrate its flexibility in terms of its location, scale and shape parameters.
2
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Beta transmuted Lomax distribution with applications

100%
Hurairah A., Alabid A.
Statistics in Transition new series
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2020
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vol. 21
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issue 2
13-34
EN
In this paper we propose and test a composite generalizer of the Lomax distribution .The genesis of the beta distribution and transmuted map is used to develop the so-called beta transmuted Lomax (BTL) distribution. The properties of the distribution are discussed and explicit expressions are derived for the moments, mean deviations, quantiles, distribution of order statistics and reliability. The maximum likelihood method is used for estimating the model parameters, and the finite sample performance of the estimators is assessed by simulation. Finally, the authors demonstrate the usefulness of the new distribution in analysing positive data.
3
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Record data from Kies distribution and related statistical inferences

100%
Al-Olaimat N. M., Bayoud H. A., Raqab M. Z.
Statistics in Transition new series
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2021
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vol. 22
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issue 4
153-170
EN
The Kies probability model was proposed as an alternative to the extendedWeibull models as it provides a more efficient fit to some real-life data sets in comparison to the aforementioned models. The paper proposes classical and Bayesian inferences for the Kies distribution based on records. Maximum likelihood estimates are studied jointly with asymptotic and bootstrap confidence intervals. Moreover, Bayes estimates, along with credible intervals are discussed assuming squared and LINEX loss functions. The proposed estimation methods have been investigated and compared via simulation studies. A real data set has been analysed for illustrative purposes.
4
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The length-biased power hazard rate distribution: Some properties and applications

100%
Mustafa A., Khan M. I.
Statistics in Transition new series
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2022
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vol. 23
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issue 2
1-16
EN
In this article, the length-biased power hazard rate distribution has introduced and investigated several statistical properties. This distribution reports an extension of several probability distributions, namely: exponential, Rayleigh, Weibull, and linear hazard rate. The procedure of maximum likelihood estimation is taken for parameters. Finally, the applicability of the model is explored by three real data sets. To examine, the performance of the technique, a simulation study is extracted.
5
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The Half-Logistic Odd Power Generalized Weibull-G Family of Distributions

88%
Peter P. O., Chipepa F., Oluyede B., Makubate B.
Central European Journal of Economic Modelling and Econometrics
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2022
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issue 1
6
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Transmuted Kumaraswamy Distribution

88%
Khan M. S., King R., Hudson I. L.
Statistics in Transition new series
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2016
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vol. 17
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issue 2
183-210
EN
The Kumaraswamy distribution is the most widely applied statistical distribution in hydrological problems and many natural phenomena. We propose a generalization of the Kumaraswamy distribution referred to as the transmuted Kumaraswamy (T K w) distribution. The new transmuted distribution is developed using the quadratic rank transmutation map studied by Shaw et al. (2009). A comprehensive account of the mathematical properties of the new distribution is provided. Explicit expressions are derived for the moments, moment generating function, entropy, mean deviation, Bonferroni and Lorenz curves, and formulated moments for order statistics. The T K w distribution parameters are estimated by using the method of maximum likelihood. Monte Carlo simulation is performed in order to investigate the performance of MLEs. The flood data and HIV/ AIDS data applications illustrate the usefulness of the proposed model.
7
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Type II Exponentiated Half-Logistic-Gompertz Topp-Leone-G Family of Distributions with Applications

88%
Oluyede B., Moakofi T.
Central European Journal of Economic Modelling and Econometrics
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2022
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issue 4
8

Empirical Analysis of Volatility and Co-movements in Serbian Frontier Financial Market: MGARCH Approach

88%
Minović J.
South East European Journal of Economics and Business
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2010
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vol. 5
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issue 1
39-55
EN
This article presents an empirical calculation of volatility and co-movements for selected securities listed at the Belgrade Stock Exchange (www.belex.rs). It applied multivariate GARCH (MGARCH) models to the analysis of comovements in the Serbian frontier financial market. For the empirical work, bivariate and trivariate versions of the restricted BEKK, DVEC, and CCC models were used. Empirical results showed that MGARCH models overcome the usual concept of the time invariant correlation coefficient. Additionaly, the results show that the conditional variances and covariances between returns on the Serbian financial market exhibit significant changes over time.
9
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Generalised Odd Frechet Family of Distributions: Properties and Applications

88%
Marganpoor S., Ranjbar V., Alizadeh M., Abdollahnezhad K.
Statistics in Transition new series
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2020
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vol. 21
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issue 3
109-128
EN
A new distribution called Generalized Odd Fréchet (GOF) distribution is presented and its properties explored. Some structural properties of the proposed distribution, including the shapes of the hazard rate function, moments, conditional moments, moment generating function, skewness, and kurtosis are presented. Mean deviations, Lorenz and Bonferroni curves, Rényi entropy, and the distribution of order statistics are given. The maximum likelihood estimation technique is used to estimate the model parameters, and finally applications of the model to a real data set are presented to illustrate the usefulness of the proposed distribution.
10
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A new count data model applied in the analysis of vaccine adverse events and insurance claims

88%
Dar S. A., Hassan A., Ahmad P. B., Wani S. A.
Statistics in Transition new series
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2021
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vol. 22
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issue 3
157-174
EN
The article presents a new probability distribution, created by compounding the Poisson distribution with the weighted exponential distribution. Important mathematical and statistical properties of the distribution have been derived and discussed. The paper describes the proposed model's parameter estimation, performed by means of the maximum likelihood method. Finally, real data sets are analyzed to verify the suitability of the proposed distribution in modeling count data sets representing vaccine adverse events and insurance claims.
11
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Zero-modified Poisson-Modification of Quasi Lindley distribution and its application

88%
Tharshan R., Wijekoon P.
Statistics in Transition new series
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2022
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vol. 23
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issue 4
113-128
EN
The Poisson-Modification of Quasi Lindley (PMQL) distribution is a newly introduced mixed Poisson distribution for over-dispersed count data. The aim of this article is to introduce the Zero-modified PMQL (ZMPMQL) distribution as an alternative to the PMQL distribution in order to accommodate zero inflation/deflation. The method of obtaining the ZMPMQL distribution jointly with some of its important properties, namely the probability mass and distribution functions, mean, variance, index of dispersion, and quantile function are presented. Furthermore, some of its special cases are discussed. The maximum likelihood (ML) estimation method is used for the unknown parameter estimation. A simulation study is conducted in order to evaluate the asymptotic theory of the ML estimation method and to show the superiority of the ML method over the method of moments estimation. The applicability of the introduced distribution is illustrated by using a real-world data set.
12
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The odd power generalized Weibull-G power series class of distributions: properties and applications

88%
Oluyede B., Moakofi T., Chipepa F.
Statistics in Transition new series
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2022
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vol. 23
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issue 1
89-108
EN
We develop a new class of distributions, namely, the odd power generalizedWeibull-G power series (OPGW-GPS) class of distributions. We present some special classes of the proposed distribution. Structural properties, have also been derived. We conducted a simulation study to evaluate the consistency of the maximum likelihood estimates. Moreover, two real data examples on selected data sets, to illustrate the usefulness of the new class of distributions. The proposed model outperforms several non-nested models on selected data sets.
13
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Generalized extended Marshall-Olkin family of lifetime distributions

88%
Goldoust M., Mohammadpour A.
Statistics in Transition new series
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2022
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vol. 23
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issue 1
55-74
EN
We introduce a new generalized family of nonnegative continuous distributions by adding two extra parameters to a lifetime distribution, called the baseline distribution, by twice compounding a power series distribution. The new family, called the lifetime power series-power series family, has a serial arrangement of parallel structures, which extends the Marshall and Olkin structure. Four special models are discussed. A mathematical treatment of the new distributions is provided, including ordinary and incomplete moments, quantile, moment generating and mean residual functions. The maximum likelihood estimation technique is used to estimate the model parameters and a simulation study is conducted to investigate the performance of the maximum likelihood estimates. Its applicability is also illustrated by means of two real data sets.
14
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O aproksymacjach funkcji przejścia dla jednowymiarowych procesów dyfuzji

75%
Szczepocki P.
Przegląd Statystyczny
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2016
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vol. 63
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issue 2
173-190
EN
Estimation methods for stochastic differentia equations driver by discretely sampled continuous diffusion processes may be split into two categories: maximum likelihood methods and methods based on the general method of moments. Usually, one does not know neither likelihood function nor theoretical moments of diffusion process and cannot construct estimators. Therefore many methods was developed to approximating unknown transition density. The aim of article is to compare properties of selected approaches, indicate their merits and limitations.
PL
Metody estymacji parametrów stochastycznych równań różniczkowych dla ciągłych procesów dyfuzji obserwowanych w dyskretnych odstępach czasu można podzielić na dwie kategorie: metody oparte na maksymalizacji funkcji wiarygodności i wykorzystujące uogólnioną metodę momentów. Zazwyczaj nie znamy jednak gęstości przejścia potrzebnej do konstrukcji funkcji wiarygodności, ani odpowiedniej ilości momentów teoretycznych, aby skonstruować odpowiednią liczbę warunków. Dlatego powstało wiele metod, które próbują przybliżyć nieznaną funkcję przejścia. Celem artykułu jest porównanie własności wybranych metod aproksymacji jednowymiarowych jednorodnych procesów dyfuzji.
15
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Relationships for moments of the progressively Type-II right censored order statistics from the power Lomax distribution and the associated inference

75%
Saran J., Pushkarna N., Sehgal S.
Statistics in Transition new series
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2021
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vol. 22
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issue 4
191-212
EN
In this paper, we establish several recurrence relations between single and product moments of progressively Type-II right censored order statistics from the power Lomax distribution. The relations enable the computation of all the single and product moments of progressively Type-II right censored order statistics for all sample sizes ?? and all censoring schemes (R1, R2, ..., Rm) m ≤ n in a simple recursive manner. The maximum likelihood approach is used for the estimation of the parameters and the reliability characteristic. A Monte Carlo simulation study has been conducted to compare the performance of the estimates for different censoring schemes.
16
Content available remote

Scaled Consistent Estimation of Regression Parameters in Frailty Models

63%
Bednarski T., Skolimowska-Kulig M.
Acta Universitatis Lodziensis. Folia Oeconomica
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2018
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vol. 5
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issue 338
133-142
PL
W artykule omówiono atrakcyjną obliczeniowo metodę estymacji parametrów dla klasy modeli regresyjnych z nieobserwowaną zmienną „frailty”. Dowiedziono, że estymator największej wiarygodności stosowany w klasycznym wykładniczym modelu regresji jest Fisherowsko zgodny z dokładnością do skali w rozważanym modelu „frailty”. Przeprowadzone badania symulacyjne oraz analiza rzeczywistych danych wskazują na dobre własności asymptotyczne prezentowanej metody estymacji.
EN
A computationally attractive method of estimation of parameters for a class of frailty regression models is discussed. The method uses maximum likelihood estimation for the classical exponential regression model. Scaled Fisher consistency is shown to hold and a simulation study indicating good asymptotic properties of the method, as well as real data case analysis, are presented.
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