T. V. Ramanathan

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An Overview of FIGARCH and Related Time Series Models

Maryam Tayefi, T. V. Ramanathan, Maryam Tayefi, 2016 .

Probabilistic frontier regression models for binary type output data

T. V. Ramanathan, Meena Badade, 2019 .

A stochastic frontier regression model with dynamic frontier

Bovas Abraham, T. V. Ramanathan, Neelabh Rohan, 2020, Commun. Stat. Simul. Comput..

Comparative Evaluation of Statistical Orbit Determination Algorithms for Short-Term Prediction of Geostationary and Geosynchronous Satellite Orbits in NavIC Constellation

Radhika A. Chipade, T. V. Ramanathan, 2021 .

The Focused Information Criterion for Logistic Time Series Regression Models Under Locally Biased Estimating Functions

T. V. Ramanathan, S. C. Pandhare, 2021 .

Coherent Forecasting in Integer-Valued AR(1) Models with Geometric Marginals

T. V. Ramanathan, Manik Awale, Mohan Kale, 2021 .

Extended Kalman filter based statistical orbit determination for geostationary and geosynchronous satellite orbits in BeiDou constellation

Radhika A. Chipade, T. V. Ramanathan, 2021 .

Forecasting overdispersed INAR(1) count time series with negative binomial marginal

T. V. Ramanathan, Manik Awale, Akanksha S. Kashikar, 2021, Commun. Stat. Simul. Comput..

Acceptance sampling plans by variables for a class of symmetric distributions

R. P. Suresh, T. V. Ramanathan, R. Suresh, 1997 .

Portfolio optimization based on modified expected shortfall

T. V. Ramanathan, Deepak K Jadhav, 2019, Studies in Economics and Finance.

Integer autoregressive models with structural breaks

T. V. Ramanathan, Neelabh Rohan, Akanksha S. Kashikar, 2013 .

Nonparametric Capability Indices

Bovas Abraham, T. V. Ramanathan, A. D. Dharmadhikari, 2003 .

Testing the constancy of the thinning parameter in a random coefficient integer autoregressive model

N. Balakrishna, T. V. Ramanathan, Manik Awale, 2019 .

Optimal estimation in random coefficient regression models

M. B. Rajarshi, T. V. Ramanathan, 1992 .

Geometric ergodicity of asymmetric volatility models with stochastic parameters

T. V. Ramanathan, N. Rohan, 2013 .

Modified Estimators of the Expected Shortfall

T. V. Ramanathan, U. Naik-Nimbalkar, Deepak K Jadhav, 2009 .

Probabilistic Frontier Regression Models for Count Type Output Data

T. V. Ramanathan, Meena Badade, 2022, Journal of Quantitative Economics.

Probabilistic frontier regression model for multinomial ordinal type output data

T. V. Ramanathan, Meena Badade, 2020, Journal of Productivity Analysis.

Rank Test for Testing Randomness of the Technology Parameters in a Stochastic Frontier Regression Model

T. V. Ramanathan, C. Ghadge, 2010, Commun. Stat. Simul. Comput..

The robust focused information criterion for strong mixing stochastic processes with L 2 -differentiable parametric densities

T. V. Ramanathan, S. Pandhare, 2020 .

The robust desparsified lasso and the focused information criterion for high-dimensional generalized linear models

T. V. Ramanathan, S. Pandhare, 2022, Statistics.

Probabilistic frontier regression model for multinomial ordinal type output data

T. V. Ramanathan, Meena Badade, 2020, Journal of Productivity Analysis.

ORDER SELECTION IN ARMA MODELS USING THE FOCUSED INFORMATION CRITERION

T. V. Ramanathan, N. Rohan, 2011 .

Asymmetric Volatility Models with Structural Breaks

T. V. Ramanathan, T. V. Ramanathan, Neelabh Rohan, 2012, Commun. Stat. Simul. Comput..

Quantification of Operational Risk: Statistical Insights on Coherent Risk Measures

T. V. Ramanathan, P. Gonpot, Dany Ng Cheong Vee, 2019, Journal of Operational Risk.

Parametric and non-parametric estimation of value-at-risk

T. V. Ramanathan, Deepak K Jadhav, 2009 .

Rank based tests for testing the constancy of the regression coefficients against random walk alternatives

M. B. Rajarshi, T. V. Ramanathan, C. Ghadge, 2011 .

Tests for bivaroate exponentiality against bifra alternatives based on censored samples

David D. Hanagal, T. V. Ramanathan, 1998 .

On optimal prediction for stochastic processes

T. V. Ramanathan, S. Adke, 1997 .

Parameter estimation of a process driven by fractional Brownian motion : An estimating function approach

T. V. Ramanathan, U. Naik-Nimbalkar, I. Kaur, 2012 .

The robust focused information criterion for strong mixing stochastic processes with $$\mathscr {L}^{2}$$-differentiable parametric densities

T. V. Ramanathan, S. Pandhare, 2020 .

Modeling seasonal epidemic data using integer autoregressive model based on binomial thinning

T. V. Ramanathan, A. Kashikar, Manik Awale, 2020 .

The focused information criterion for stochastic model selection problems using M-estimators

T. V. Ramanathan, S. Pandhare, 2018 .

THE EFFICIENCY OF MODIFIED JACKKNIFE AND RIDGE TYPE REGRESSION ESTIMATORS: A COMPARISON

T. V. Ramanathan, S. Gore, Feras Sh, 2008 .

Nonparametric estimation of a time-varying GARCH model

T. V. Ramanathan, N. Rohan, 2013 .

Test for randomness of the technology parameter in a stochastic frontier regression model

T. V. Ramanathan, Chanchala Ghadge, T. V. Ramanathan, 2010, Stat. Methods Appl..

The focussed information criterion for generalised linear regression models for time series

T. V. Ramanathan, S. Pandhare, 2020, Australian & New Zealand Journal of Statistics.