The paper discusses penalised spline (P -spline) smoothing for hazard regression of multivariable survival data. Non-proportional hazard functions are fitted in a numerically handy manner by employing Poisson regression which results from numerical integration of the cumulative hazard function. Multivariate smoothing parameters are selected by utilizing the connection between P -spline smoothin...

Twitter is one among the fastest growing social networking services. This growth has led to an increase in Twitter scams (e.g., intentional deception). There is relatively little effort in identifying scams in Twitter. In this paper, we propose a semisupervised Twitter scam detector based on a small labeled data. The scam detector combines selflearning and clustering analysis. A suffix tree dat...

The optimum s-gradient method for minimizing a positive definite quadratic function f(x) on En has long been known to converge for s > 1 . For these s the author studies the directions from which the iterates Xk approach their limit, and extends to s > 1 a theory proved by Akaike for s=l. It is shown that f(xk) can never converge to its minimum value faster than linearly, except in degenerate c...

The asymptotic efficiency of the indirect estimation methods, such as the efficient method of moments and indirect inference, depends on the choice of the auxiliary model. Up to date, this choice is somehow ad hoc and based on an educated guess of the researcher. In this article we develop three information criteria that help the user to optimize the choice among nested and non–nested auxiliary...

Consider the problem of modeling hysteresis for finite-state random walks using higher-order Markov chains. This Letter introduces a Bayesian framework to determine, from data, the number of prior states of recent history upon which a trajectory is statistically dependent. The general recommendation is to use leave-one-out cross validation, using an easily-computable formula that is provided in...

The asymptotic behaviour of a family of gradient algorithms (including the methods of steepest descent and minimum residues) for the optimisation of bounded quadratic operators in R and Hilbert spaces is analyzed. The results obtained generalize those of Akaike (1959) in several directions. First, all algorithms in the family are shown to have the same asymptotic behaviour (convergence to a two...

In our present study, GARCH family models are used for modeling and forecasting the rice yield of four provinces of Pakistan during the period of 1947-48 to 2008-09. Also Auto regressive, moving average and Autoregressive moving average models are described. Thus, the selected GARCH models for all provinces are also presented for forecasting purpose on the basis of two criteria AIC (Akaike info...

This paper introduces an information theoretic model selection and ridge parameter estimation criterion for generalized linear models based on the minimum message length principle. The criterion is highly general in nature, and handles a range of target distributions, including the normal, binomial, Poisson, geometric and gamma distributions. Estimation of the regression parameters, the ridge h...

In this paper, the generalized gamma (GG) distribution that is a flexible distribution in statistical literature, and has exponential, gamma, and Weibull as subfamilies, and lognormal as a limiting distribution is introduced. The power and logarithmic moments of this family is defined. A new moment estimation method of parameters of GG family using it’s characterization is presented, this metho...

We suggest a model in which theories are ranked given various databases. Certain axioms on such rankings imply a numerical representation that is the sum of the log-likelihood of the theory and a fixed number for each theory, which may be interpreted as a measure of its complexity. This additive combination of log-likelihood and a measure of complexity generalizes both the Akaike Information Cr...