Interventions in ingarch processes (2009)
Fokianos, Konstantinos, Fried, Roland
We study the problem of intervention effects generating various types of outliers in a linear count time series model. This model belongs to the class of observation driven models and extends the...
Comparing two samples by penalized logistic regression (2008)
Inference based on the penalized density ratio model is proposed and studied. The model under consideration is specified by assuming that the log--likelihood function of two unknown densities is of...
Professional & Teaching Experience (2008)
Konstantinos Fokianos, Konstantinos Fokianos Page
website: www.ucy.ac.cy/˜fokianos
Dissertation Title: \Categorical Time Series: Prediction and Control" (2007)
Konstantinos Fokianos, Benjamin Kedem
{ Studied partial likelihood asymptotic theory for regression models for nonstationary categorical time series. The results were applied to rainfall data. { Studied a logistic regression model for...
MERGING INFORMATION FOR SEMIPARAMETRIC DENSITY ESTIMATION (2007)
Abstract. The density ratio model specifies that the likelihood ratio of m 1 probability density functions with respect to the m'th is of known parametric form without reference to any...
Power Divergence Family of Tests for Categorical Time Series Models (2007)
A fundamental issue that arises after fitting a regression model is that of testing the goodness of the fit. Our work brings together the power divergence family of goodness of fit tests and...
Identifying periodically expressed transcripts in microarray time series data (2004)
Wichert, Sofia, Fokianos, Konstantinos, Strimmer, Korbinian
Motivation: Microarray experiments are now routinely used to collect large-scale time series data, for example to monitor gene expression during the cell cycle. Statistical analysis of this data...
Regression Theory for Categorical Time Series (2003)
Fokianos, Konstantinos, Kedem, Benjamin
Categorical---or qualitative---time series data with random time-dependent covariates are frequently encountered in diverse applications as the list of examples shows. As with "ordinary'' time...
Regression Models for Time Series Analysis (2002)
Kedem, Benjamin, Fokianos, Konstantinos
0-471-36355-3
A Generalized Moments Specification Test for the Logistic Link (2000)
Konstantinos Fokianos, Amy Peng, Jing Qin
The authors consider the problem of testing the validity of the logistic regression model using a random sample. Given the values of the response variable, they observe that the sample actually...
Categorical time series :--prediction and control /--by Konstantinos Fokianos. (1996)
Thesis research directed by Dept. of Mathematics.
Exceedances and Moments in Data Containing Zeros (1996)
Fokianos, Konstantinos, Kedem, Benjamin, Short, D.A.
Rain rate-the speed of rain in mm/hr-assumes zero values when it is not raining, and positive values on a continuum otherwise. For large areas, empirical evidence points to a high correlation between...
Recursive Estimation for Time Series Following Generalized Linear Models (1996)
Fokianos, Konstantinos, Kedem, Benjamin
A recursive estimation method for time series models following generalized linear models is studied in two ways. The estimation procedure, suitably modified, gives rise to a stochastic approximation...
Prediction and Classification of Non-stationary Categorical Time Series (1996)
Fokianos, Konstantinos, Kedem, Benjamin
Partial Likelihood analysis of a general regression model for the analysis of non-stationary categorical time series is presented, taking into account stochastic time dependent covariates. The model...
On Combining Instruments (1996)
Fokianos, Konstantinos, Kedem, Benjamin, Qin, J., Haferman, Jeffrey L., Short, D.A.
Suppose two instruments Io and I1 measure the same quantity with the same resolution, where it is know Io is more reliable. The second, I1 , is assumed a distortion of Io in some sense. A method is...
Categorical Time Series: Prediction and Control (1996)
We study regression models for nonstationary categorical time series and their applications, and address the issues of prediction, estimation and control. Generalized Linear Models and Partial...
Merging information for semiparametric density estimation
The density ratio model specifies that the likelihood ratio of "m" - 1 probability density functions with respect to the "m"th is of known parametric form without reference to any parametric model....
Partial Likelihood Inference For Time Series Following Generalized Linear Models
Konstantinos Fokianos, Benjamin Kedem
The present article offers a certain unifying approach to time series regression modelling by combining partial likelihood (PL) inference and generalized linear models. An advantage gained by...
Power Divergence Family of Tests for Categorical Time Series Models
Stochastic time dependent covariates, partial likelihood, martingale, logistic regression, multinomial logits, proportional odds, power,
On the Effect of Misspecifying the Density Ratio Model
Konstantinos Fokianos, Irene Kaimi
Biased sampling, Empirical likelihood, Box–Cox transformation, Mean square error, Bias, Power,
Prediction and Classification of Non-stationary Categorical Time Series
Fokianos, Konstantinos, Kedem, Benjamin
Partial likelihood analysis of a general regression model for the analysis of non-stationary categorical time series is presented, taking into account stochastic time dependent covariates. The model...
Konstantinos Fokianos, Anders Rahbek, Dag Tjøstheim
This paper considers geometric ergodicity and likelihood based inference for linear and nonlinear Poisson autoregressions. In the linear case the conditional mean is linked linearly to its past...
Konstantinos Fokianos, Anders Rahbek, Dag Tjøstheim
This paper considers geometric ergodicity and likelihood based inference for linear and nonlinear Poisson autoregressions. In the linear case the conditional mean is linked linearly to its past...
Konis, Kjell, Fokianos, Konstantinos
An important problem in logistic regression modeling is the existence of the maximum likelihood estimators. In particular, when the sample size is small, the maximum likelihood estimator of the...