# T. V. RamanathanSavitribai Phule Pune University | University of Poona · Department of Statistics

T. V. Ramanathan

Ph.D.

## About

47

Publications

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488

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December 2005 - November 2015

## Publications

Publications (47)

The classical lasso estimation for sparse, high-dimensional regression models is typically biased and lacks the oracle properties. The desparsified versions of the lasso have been proposed in the literature that attempt to overcome these drawbacks. In this paper, we propose the outliers-robust version of the desparsified lasso for high dimensional...

This paper proposes a Conway-Maxwell-Poisson (COM-Poisson) probabilistic frontier regression model for count type output data addressing the dispersion in the data. We consider some of the outcomes as desired outcomes or ‘interest class’, and a change in the probability of output falling into this class is attributed to the decrease in the decision...

Statistical modeling of biomedical data arising from the cytologic samples collected during cancer trials often involves the analysis of binary time series responses indicating the status of the samples being benign or malignant. The model selection problems pertaining to such data involve exploring the Markovian dependence of the status of the cyt...

This paper addresses the coherent forecasting problem for overdispersed integer-valued autoregressive (INAR) model of order one having negative binomial marginal distribution. INAR models with Poisson or geometric marginal distribution have been used by several researchers to tackle the forecasting and related issues in low count time series. Howev...

The present paper proposes the focussed information criterion (FIC) to tackle the model selection problems pertinent to generalised linear models (GLM) for time series. As a first step towards constructing the FIC, we formally discuss the local asymptotic theory of quasi-maximum likelihood estimation for time series GLM under potential model misspe...

This paper proposes a probabilistic frontier regression model for multinomial ordinal type output data. We consider some of the output categories as ‘categories of interest’ and the reduction in probability of an output falling into these categories is attributed to the lack in technical efficiency (TE) of the decision-making unit. A measure for TE...

Claeskens and Hjort (J Am Stat Assoc 98(464):900–916, 2003) constructed the focused information criterion (FIC) using maximum likelihood estimators to facilitate the contextual selection of probability models for independently distributed observations. We generalize these results to the case of stationary, strong mixing stochastic processes exhibit...

Integer-valued autoregressive models are widely used for modeling the time dependent count data. Many of the inference problems related to these types of models are not yet addressed due to the complexities of the related distribution theory. In this paper, we consider one such inference problem associated with these types of models. For a random c...

Purpose
An investor is expected to analyze the market risk while investing in equity stocks. This is because the investor has to choose a portfolio which maximizes the return with a minimum risk. The mean-variance approach by Markowitz (1952) is a dominant method of portfolio optimization, which uses variance as a risk measure. The purpose of this...

This paper proposes a probabilistic frontier regression model for binary type output data in a production process setup. We consider one of the two categories of outputs as ‘selected’ category and the reduction in probability of falling in this category is attributed to the reduction in technical efficiency (TE) of the decision-making unit. An effi...

This paper reviews the recent literature on conditional duration modeling in high-frequency finance. These conditional duration models are associated with the time interval between trades, price, and volume changes of stocks, traded in a financial market. An earlier review by Pacurar provides an exhaustive survey of the first and some of the second...

Community-based groups (CBGs) are a frequent feature of community mobilization. In HIV/AIDS prevention programs in India, CBGs and networks are seen as a vehicle to strengthen demand for services and manage programmatic activities. Community mobilization is an important component of a participatory approach to health and development interventions.¹...

Recently, there has been a growing interest in studying the autoregressive conditional duration (ACD) models, originally introduced by (Engle, R. F., and J. R. Russell. 1998. “Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data. Econometrica 66: 1127–1162). ACD models are useful for modeling the time between the...

Stochastic conditional duration models are widely used in the financial econometrics literature to model the duration between transactions in a financial market. Even though there are developments in terms of modelling aspects, estimation, filtering and smoothing are still being investigated by researchers in this area. Almost all the existing proc...

We consider a stochastic frontier regression model with a time dependent efficiency process, which is assumed to follow an exponential autoregressive sequence. The likelihood for the model is derived in the context of a bivariate exponential distribution. Bayesian method is suggested for the estimation of parameters. We apply the model and the esti...

The coherent risk measure expected shortfall is a popular alternative to value-at-risk. However, the estimated value may miscommunicate the actual risk, especially when huge losses are present in the return series. This may force the financial institution to keep extra capital to meet the requirement set by the regulators. We propose a new robust c...

Even though integer-valued time series are common in practice, the methods for their analysis have been developed only in recent past. Several models for stationary processes with discrete marginal distributions have been proposed in the literature. Such processes assume the parameters of the model to remain constant throughout the time period. How...

In this paper, a non-stationary time-varying GARCH (tvGARCH) model has been introduced by allowing the parameters of a stationary GARCH model to vary as functions of time. It is shown that the tvGARCH process is locally stationary in the sense that it can be locally approximated by stationary GARCH processes at fixed time points. We develop a two-s...

In this paper, we consider a general family of asymmetric volatility models with stationary and ergodic coefficients. This family can nest several non-linear asymmetric GARCH models with stochastic parameters into its ambit. It also generalizes Markovswitching GARCH and GJR models. The geometric ergodicity of the proposed process is established. Su...

This article develops an asymmetric volatility model that takes into consideration the structural breaks in the volatility process. Break points and other parameters of the model are estimated using MCMC and Gibbs sampling techniques. Models with different number of break points are compared using the Bayes factor and BIC. We provide a formal test...

Community mobilisation is an important component of a participatory approach to health and development interventions. However, it is challenging to define, measure and assess community participation and ownership of a programme, especially at scale.
An iterative cross-sectional survey was designed for implementation across a representative sample o...

In a participatory approach to health and development interventions, defining and measuring community mobilisation is important, but it is challenging to do this effectively, especially at scale.
A cross-sectional, participatory monitoring tool was administered in 2008-2009 and 2009-2010 across a representative sample of 25 community-based groups (...

This paper reviews the theory and applications related to fractionally integrated generalized autoregressive conditional heteroscedastic (FIGARCH) models, mainly for describing the observed persistence in the volatility of a time series. The long memory nature of FIGARCH models allows to be a better candidate than other conditional heteroscedastic...

A class of approximately locally most powerful type tests based on ranks of residuals is suggested for testing the hypothesis that the regression coefficient is constant in a standard regression model against the alternatives that a random walk process generates the successive regression coeﬃcients. We derive the asymptotic null distribution of suc...

This paper develops a new approach for order selection in autoregressive moving average models using the focused information criterion. This criterion minimizes the asymptotic mean squared error of the estimator of a parameter of interest. Simulation studies indicate that the suggested criterion is quite effective and comparable to the Akaike infor...

This paper develops a new approach for the order selection in the ARMA models using focused information criterion (FIC). This criterion essentially minimizes the MSE of the estimates of the parameter of interest using their asymptotic theory. We discuss the order selection of ARMA and AR models using FIC, under various estimation procedures, such a...

We propose a class of rank tests for testing the randomness of technology parameters in a stochastic frontier regression model. The asymptotic distribution of the test statistic is derived using the weak convergence results of empirical and rank processes. Since the distribution is quite complex and involves the unknown distribution of the error te...

This paper considers the problem of testing for randomness of the technology parameter in a stochastic frontier regression
model. A test statistic is proposed and its asymptotic distribution theory is discussed. Simulation results show that the
proposed test maintains its level and also quite powerful against various alternatives. An empirical inve...

In ridge regression, the estimation of ridge parameter k is an important problem. There are several methods available in the literature to do this job some what efficiently. However, no attempts were made to suggest a confidence interval for the ridge parameter using the knwoledge from the data. In this article, we propose a data dependent confiden...

The coherent risk measure Expected Shortfall is popularly considered as an alternative to Value-at-Risk. We briefly review all existing parametric and non-parametric methods to estimate Expected Shortfall. The historical method is considered as the best method of estimation for the Expected Shortfall, though it has a serious disadvantage of over-es...

In this paper, we derive the density and distribution functions of the estimator of the shrinkage parameters of the Liu and generalized Liu estimators associated with the normal linear regression model. We indicate how these distributions can be used in arriving at a confidence interval for the optimal value of the shrinkage parameter. Since the di...

Value-at-risk (VaR) is one of the most common risk measures used in finance. The correct estimation of VaR is essential for any financial insti-tution, in order to arrive at the accurate capital requirements and to meet the adverse movements of the market. We give a brief review of all of the existing parametric and non-parametric methods of estima...

A common problem in multiple regression models is multicollinearity, which produces undesirable effects on the least squares estimator. To circumvent this problem, two well known estimation procedures are often suggested in the literature. They are the generalized ridge regression (GRR) estimation suggested by A. E. Hoerl and R. W. Kennard [Technom...

For some reliability systems, it is possible to have the system reliability smaller than the reliability obtained using the configuration of the components. This may be due to the inefficiency of the system. By inefficiency, we mean any tendency or attribute that will bring down the performance of the system from the level the configuration is capa...

An attempt is made here to construct and present relative efficiency indices for the services rendered by health districts and specific hospitals in Botswana, using Stochastic Frontier Regression analysis and Data Envelopment Analysis. The analysis indicated that three districts - Kweneng East, Kgalagadi and Boteti - have efficiency scores below th...

The process capability indices C p and C pk are widely used in statistical quality control to assess the capability of a process. These indices are defined, based on the assumption that the quality characteristic follows a normal distribution. In this paper two new capability indices are considered, which do not depend on any distributional assumpt...

We develop a test procedure to test the hypothesis that the distribution of the lifetime is bivariate exponential of Marshall and Olkin against that it is bivariate increasing failure rate average when the sample is of the type univariate or bivariate randomly censored.

This paper discusses an approximate score test for testing randomness of environments in a branching process without observing
the environments. Using an appropriate martingale central limit theorem the asymptotic null distribution of test statistic
is shown to be normal. When the offspring distribution is Poisson, the detail derivation of asymptot...

The problem of prediction is concerned with predicting an unobserved random variable using a data dependent statistic. We extend the Rao-Blackwell theorem of Johansson (Scand. J. Statist. (1990) 17, 135–145) in the prediction context to an arbitrary convex loss function. Two situations in which the problem of obtaining an unbiased predictor with mi...

We develop the score test for the hypothesis that a parameter of a Markov sequence is constant over time, against the alternatives that it varies over time, i.e., theta(l) = theta + U-t ; t = 1,2,..., where {U-l; t = 1,2,...} is a sequence of independently and identically distributed random variables with mean zero and variance sigma(u)(2) > 0 and...

The estimation of percentage defectives using a normal sampling plan will not be appropriate when the assumption of normality is violated. In this paper, we propose a sampling plan based on a more general symmetric family of distributions with the parameters estimated using the modified maximum likelihood (MML) procedures introduced by Tiku and Sur...

In linear regression models with random coefficients, the score function usually involves unknown nuisance parameters in the form of weights. Conditioning with respect to the sufficient statistics for the nuisance parameter, when the parameter of interest is held fixed, eliminates the nuisance parameters and is expected to give reasonably good esti...

We propose a class of nonparametric tests for testing non-stochasticity of the regression parameterβ in the regression modely
i
=βx
i
+ɛ
i
,i=1, ...,n. We prove that the test statistics are asymptotically normally distributed both underH
0 and under contiguous alternatives. The asymptotic relative efficiencies (in the Pitman sense) with respect to...

The solution to the functional equation for the stationary distribution of random coefficient autoregressive models is not tractable except in a few cases. We therefore attempt approximations to the exact stationary distribution by members of a family of distributions via moments. These approximations appear not to be very satisfactory in the case...

An important issue associated with stochastic frontier analysis is that of choosing an appropriate model for the inefficiency component, which is non negative and right skewed. Inefficiency is usually modeled by a random variable with an asymmetric distribution, characterized by one or two parameters. In this paper we have considered inverse Gaussi...