- Lucknow, U.P. India
- Maharshi Dayanand University, Department of Statistics, Faculty Memberadd
Research Interests:
In developmental studies, the infrastructural sector is considered as an important component of overall economic development. The infrastructural growth in the state of Uttar Pradesh is undoubtedly critical since independence. The main... more
In developmental studies, the infrastructural sector is considered as an important component of overall economic development. The infrastructural growth in the state of Uttar Pradesh is undoubtedly critical since independence. The main focus of this paper is to uncover the principal factors or dimensions of infrastructural characteristics and to quantify the level of infrastructural development of Uttar Pradesh into five clusters having different grade of development using Exploratory Factor Analysis & K-means Cluster Analysis. The analysis has been carried out by taking into account various infrastructural indicators for the time period of two years from 2018 to 2019. The results of the present analysis led to the identification of the five factors of infrastructural characteristics, and the classification of all the seventy-five districts of Uttar Pradesh into five regions with different degree of infrastructural development. The ‘infrastructural regions’ uncovered through this pr...
Research Interests:
This article deals with the estimation of parameters and reliability characteristics of Lindley distribution underrandom censoring. Expected time on test based on randomly censored data is obtained. The maximum likelihood estimators of... more
This article deals with the estimation of parameters and reliability characteristics of Lindley distribution underrandom censoring. Expected time on test based on randomly censored data is obtained. The maximum likelihood estimators of the unknown parameters and reliability characteristics are derived. The asymptotic, bootstrap p and bootstrap t confidence intervals of the parameters are constructed. The Bayes estimators of the parameters and reliability characteristics under squared error loss function using non-informative and gamma informative priors are obtained. For computing of Bayes estimates, Lindley approximation and MCMC methods are considered. Highest posterior density (HPD) credible intervals of the parameters are obtained using MCMC method. Various estimation procedures are compared using a Monte Carlo simulation study. Finally, a real data set is analyzed for illustration purposes.
Research Interests:
Anopheles stephensi is the main vector of urban malaria in South Asia. Three ecological variants (‘type’, ‘mysorensis’and‘intermediate’) of An. stephensi have been reported on the basis of ecology and egg morphology. However, it is... more
Anopheles stephensi is the main vector of urban malaria in South Asia. Three ecological variants (‘type’, ‘mysorensis’and‘intermediate’) of An. stephensi have been reported on the basis of ecology and egg morphology. However, it is unclear if there is any genetic isolation between the three variants. We analyzed the three variants of An. stephensi using eight microsatellite loci and found that large and significant genetic differentiation exists between them (mean FST= 0.393 and mean RST= 0.422). Pairwise estimates of genetic differentiation between the variants were ‘type’ versus ‘mysorensis’ (mean FST= 0.411 and mean RST= 0.308), ‘type’ versus ‘intermediate’ (mean FST= 0.388 and mean RST= 0.518) and ‘intermediate’ versus ‘mysorensis’ (mean FST= 0.387 and mean RST= 0.398) and all were statistically significant (P < 0.05). The greater sensitivity of RST in differentiation indicated that mutations and not genetic drift had generated the differences between three variants of An. st...
Research Interests:
Background: Mumbai is one of the most populous and high HIV prevalence cities in India. It has witnessed substantial changes in HIV-risk behaviors and a decline in HIV prevalence among high-risk groups during the past decade. Aim: To... more
Background: Mumbai is one of the most populous and high HIV prevalence cities in India. It has witnessed substantial changes in HIV-risk behaviors and a decline in HIV prevalence among high-risk groups during the past decade. Aim: To examine the changing pattern in the number of new HIV infections by transmission routes in Mumbai during 2000-2017. Methods: We used the Asian Epidemic Model by dividing the adult population (aged 15 and above) into seven subgroups: brothel-based and non-brothel based female sex workers (FSWs), heterosexual clients of FSWs, men who have sex with men/transgendered people (MSM), injecting drug users (IDUs), general women and general men. The MSM subgroup included homosexual and bisexual men. Results: New HIV infections among adults reduced by 86 % during 2000-2010. The highest decline was among FSWs and their heterosexual clients (95%-98%), followed by MSM (82%), general women (77%), IDUs (51%) and general men (42%). Most new HIV infections during 2011-20...
Research Interests:
Stein-rule estimation is a well-known method to improve the unbiased OLSE in the sense of smaller Mean-Square-Error. The paper is investigating the behaviour of this efficiency relation in case of misspecification of the linear model... more
Stein-rule estimation is a well-known method to improve the unbiased OLSE in the sense of smaller Mean-Square-Error. The paper is investigating the behaviour of this efficiency relation in case of misspecification of the linear model caused by inclusion of superfluous variables
Research Interests:
HIV/AIDS- Research and Palliative Care 2012:4 141–148
The association between adolescent entry into the trucking industry and risk of HIV among long-distance truck drivers in India
Research Interests:
This article considers a linear regression model in which misspecification relates to the use of a stochastic proxy variable. The analysis indicates the decline in efficiency of the predictions arising from the ordinary least squares and... more
This article considers a linear regression model in which misspecification relates to the use of a stochastic proxy variable. The analysis indicates the decline in efficiency of the predictions arising from the ordinary least squares and the Stein-rule estimation procedures when a proxy variable is used in the place of an unobservable variable. However, the performance of the Stein-rule predictions is still found to be better than the ordinary least squares predictions over a broad range of k, the characterizing scalar of the Stein-rule estimator.
Research Interests:
The objective of this paper is to examine the performance of the mixed regression estimator (MRE) utilising incomplete prior information when there is misspecification related to inclusion of some superfluous variables. Assuming... more
The objective of this paper is to examine the performance of the mixed regression estimator (MRE) utilising incomplete prior information when there is misspecification related to inclusion of some superfluous variables. Assuming disturbances to be not necessarily normal, the conditions for the supriority of, MRE over the ordinary least squares (OLS) estimator are obtained using small disturbances asymptotic approximations.
Research Interests:
This article considers a misspecified linear regression model in which misspecification relates to the inclusion of some explanatory variables. Assuming the distribution of disturbances to be not necessarily normal, this paper... more
This article considers a misspecified linear regression model in which misspecification relates to the inclusion of some explanatory variables. Assuming the distribution of disturbances to be not necessarily normal, this paper investigates the ...
Research Interests:
ABSTRACT The article considers the predictive efficiency of some improved estimators of coefficients in linear regression models, constructed with the help of the Stein rule when there are some stochastic linear restrictions on the vector... more
ABSTRACT The article considers the predictive efficiency of some improved estimators of coefficients in linear regression models, constructed with the help of the Stein rule when there are some stochastic linear restrictions on the vector of unknown parameters. Assuming the distribution of disturbances to be not necessarily normal, an attempt is made to compare the performance of improved and mixed regression estimators in terms of their respective risks.
Research Interests:
Research Interests:
Research Interests:
In this article, estimation of stress-strength reliability $\delta=P\left(Y<X\right)$ based on progressively first failure censored data from two independent inverse Weibull distributions with different shape and scale parameters is... more
In this article, estimation of stress-strength reliability $\delta=P\left(Y<X\right)$ based on progressively first failure censored data from two independent inverse Weibull distributions with different shape and scale parameters is studied. Maximum likelihood estimator and asymptotic confidence interval of $\delta$ are obtained. Bayes estimator of $\delta$ under generalized entropy loss function using non-informative and gamma informative priors is derived. Also, highest posterior density credible interval of $\delta$ is constructed. Markov Chain Monte Carlo (MCMC) technique is used for Bayes computation. The performance of various estimation methods are compared by a Monte Carlo simulation study. Finally, a pair of real life data is analyzed to illustrate the proposed methods of estimation.
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Malaria is a major public health problem in India because climatic condition and geography of India provide an ideal environment for development of malaria vector. Anopheles stephensi is a major urban malaria vector in India and its... more
Malaria is a major public health problem in India because climatic condition and geography of India provide an ideal environment for development of malaria vector. Anopheles stephensi is a major urban malaria vector in India and its control has been hampered by insecticide resistance. In present study population genetic structure of A. stephensi is analyzed at macro geographic level using 13 microsatellite markers. Significantly high genetic differentiation was found in all studied populations with differentiation values (FST) ranging from 0.0398 to 0.1808. The geographic distance was found to be playing a major role in genetic differentiation between different populations. Overall three genetic pools were observed and population of central India was found to be coexisting in two genetic pools. High effective population size (Ne) was found in all the studied populations.
Research Interests:
Research Interests:
The article considers the predictive efficiency of some improved estimators of coefficients in linear regression models, constructed with the help of the Stein rule when there are some stochastic linear restrictions on the vector of... more
The article considers the predictive efficiency of some improved estimators of coefficients in linear regression models, constructed with the help of the Stein rule when there are some stochastic linear restrictions on the vector of unknown parameters. Assuming the distribution of disturbances to be not necessarily normal, an attempt is made to compare the performance of improved and mixed regression estimators in terms of their respective risks.
Research Interests:
This article investigates the effect on the disturbance variance estimation in linear regression models when Stein-rule instead of least squares estimation is used. Using small sigma asymptotics, it is demonstrated that the iterative... more
This article investigates the effect on the disturbance variance estimation in linear regression models when Stein-rule instead of least squares estimation is used. Using small sigma asymptotics, it is demonstrated that the iterative Stein-rule estimator is not only asymptotically biased but is also dominated by its counterpart stemming from ordinary least squares.
Research Interests:
The article considers the problem of simultaneous prediction of actual and average values of the study variable in linear regression models when some exact prior information in the form of linear restrictions binding the regression... more
The article considers the problem of simultaneous prediction of actual and average values of the study variable in linear regression models when some exact prior information in the form of linear restrictions binding the regression coefficients is available and analyses the performance properties of predictors using various improved estimators. An attempt has also been made to obtain optimal weights that minimize the predictive risks of the estimators for simultaneous prediction.
Research Interests:
The article studies and compares the performance properties of a weighted average estimator of ordinary least squares and Stein-rule considering the balanced loss functions proposed by A. Zellner [S. S. Gupta et al. (eds.), Stat. Decis.... more
The article studies and compares the performance properties of a weighted average estimator of ordinary least squares and Stein-rule considering the balanced loss functions proposed by A. Zellner [S. S. Gupta et al. (eds.), Stat. Decis. Theory Relat. Topics V. Proc. fifth Purdue Int. Symp. Stat. Decis. Theory Relat. Topics 1992, 377–390 (1994; Zbl 0787.62035)]. Superiority conditions have been derived assuming the error distribution to be non-normal.
Research Interests:
Research Interests:
Research Interests:
The objective of this paper is to examine the performance of the mixed regression estimator (MRE) utilising incomplete prior information when there is misspecification related to inclusion of some superfluous variables. Assuming... more
The objective of this paper is to examine the performance of the mixed regression estimator (MRE) utilising incomplete prior information when there is misspecification related to inclusion of some superfluous variables. Assuming disturbances to be not necessarily normal, the conditions for the supriority of, MRE over the ordinary least squares (OLS) estimator are obtained using small disturbances asymptotic approximations.
Research Interests: Statistics and Test
This article considers a linear regression model in which misspecification relates to the use of a stochastic proxy variable. The analysis indicates the decline in efficiency of the predictions arising from the ordinary least squares and... more
This article considers a linear regression model in which misspecification relates to the use of a stochastic proxy variable. The analysis indicates the decline in efficiency of the predictions arising from the ordinary least squares and the Stein-rule estimation procedures when a proxy variable is used in the place of an unobservable variable. However, the performance of the Stein-rule predictions is still found to be better than the ordinary least squares predictions over a broad range of k, the characterizing scalar of the Stein-rule estimator.
Research Interests:
The population structure of An. stephensi in North-west India was studied to assess the impact of the Aravalli Hills, as a barrier to gene flow using microsatellite markers. Large and significant genetic differentiation was found along... more
The population structure of An. stephensi in North-west India was studied to assess the impact of the Aravalli Hills, as a barrier to gene flow using microsatellite markers. Large and significant genetic differentiation was found along the sides of, as well as across, the Aravalli Hills as the mean FST and RST on west vs. east of the Aravalli Hills were 0.213, 0.112 and 0.179, 0.056, respectively. Similarly, across the hills, mean values of FST and RST were 0.100 and 0.094, respectively. Genetic diversity on both sides did not vary significantly. The FST values were more sensitive than RST values, indicating that genetic drift might have caused genetic differentiation between populations. A positive correlation (r = 0.0149 and 0.157, respective to FST and RST) was found between genetic differentiations and geographic distances irrespective of the hills. Low level of gene flow was found along both sides (Nm = 0.92 and 0.14; west vs. east of Aravalli Hills, respectively) as compared to across the Aravalli Hills (Nm = 2.25). It was found that the Aravalli Hills are not working as an effective barrier to gene flow for An. Stephensi, maybe because of the low average height and discontinuous hills, however, the distance is playing a major role for differentiation between populations due to active mode of dispersal of An. stephensi mosquitoes which have a short flight range. All this information should help draw the strategies for genetic control of mosquitoes using transgenic mosquitoes.
Research Interests:
Abstract Anopheles stephensi is the main vector of urban malaria in South Asia. Three ecological variants (‘type’, ‘mysorensis’and‘intermediate’) of An. stephensi have been reported on the basis of ecology and egg morphology. However, it... more
Abstract Anopheles stephensi is the main vector of urban malaria in South Asia. Three ecological variants (‘type’, ‘mysorensis’and‘intermediate’) of An. stephensi have been reported on the basis of ecology and egg morphology. However, it is unclear if there is any genetic isolation between the three variants. We analyzed the three variants of An. stephensi using eight microsatellite loci and found that large and significant genetic differentiation exists between them (mean FST= 0.393 and mean RST= 0.422). Pairwise estimates of genetic differentiation between the variants were ‘type’ versus ‘mysorensis’ (mean FST= 0.411 and mean RST= 0.308), ‘type’ versus ‘intermediate’ (mean FST= 0.388 and mean RST= 0.518) and ‘intermediate’ versus ‘mysorensis’ (mean FST= 0.387 and mean RST= 0.398) and all were statistically significant (P < 0.05). The greater sensitivity of RST in differentiation indicated that mutations and not genetic drift had generated the differences between three variants of An. stephensi. The present study indicated large genetic differentiation and presence of non-significant low level of gene flow between the three variants (‘type’, ‘mysorensis’and‘intermediate’) of An. stephensi.
Research Interests:
This article considers a misspecified linear regression model in which misspecification relates to the inclusion of some explanatory variables. Assuming the distribution of disturbances to be not necessarily normal, this paper... more
This article considers a misspecified linear regression model in which misspecification relates to the inclusion of some explanatory variables. Assuming the distribution of disturbances to be not necessarily normal, this paper investigates the efficiency properties of predictions arising from ordinary least squares and Stein-rule when the aim is to predict either the actual value or the mean value of the study variable.
Research Interests:
This paper considers the predictive efficiency of some improved estimators when there are exact prior restrictions on the coefficients of the linear regression model. A comparative study of various improved estimators in terms of their... more
This paper considers the predictive efficiency of some improved estimators when there are exact prior restrictions on the coefficients of the linear regression model. A comparative study of various improved estimators in terms of their respective risks is also described.