Tobias Rydén

Fast simulated annealing in $\R^d$ and an application to maximum likelihood estimation (2006)

Rubenthaler, Sylvain, Rydén, Tobias, Wiktorsson, Magnus

Using classical simulated annealing to maximise a function $\psi$ defined on a subset of $\R^d$, the probability $\p(\psi(\theta_n)\leq \psi_{\max}-\epsilon)$ tends to zero at a logarithmic rate as...

Fast simulated annealing in $\R^d$ and an application to maximum likelihood estimation (2006)

Rubenthaler, Sylvain, Rydén, Tobias, Wiktorsson, Magnus

Using classical simulated annealing to maximise a function $\psi$ defined on a subset of $\R^d$, the probability $\p(\psi(\theta_n)\leq \psi_{\max}-\epsilon)$ tends to zero at a logarithmic rate as...

Fast simulated annealing in $\R^d$ and an application to maximum likelihood estimation (2006)

Rubenthaler, Sylvain, Rydén, Tobias, Wiktorsson, Magnus

Using classical simulated annealing to maximise a function $\psi$ defined on a subset of $\R^d$, the probability $\p(\psi(\theta_n)\leq \psi_{\max}-\epsilon)$ tends to zero at a logarithmic rate as...

Fast simulated annealing in $\R^d$ and an application to maximum likelihood estimation (2006)

Rubenthaler, Sylvain, Rydén, Tobias, Wiktorsson, Magnus

Using classical simulated annealing to maximise a function $\psi$ defined on a subset of $\R^d$, the probability $\p(\psi(\theta\_n)\leq \psi\_{\max}-\epsilon)$ tends to zero at a logarithmic rate as...

Fast simulated annealing in $\R^d$ and an application to maximum likelihood estimation (2006)

Rubenthaler, Sylvain, Rydén, Tobias, Wiktorsson, Magnus

Using classical simulated annealing to maximise a function $\psi$ defined on a subset of $\R^d$, the probability $\p(\psi(\theta_n)\leq \psi_{\max}-\epsilon)$ tends to zero at a logarithmic rate as...

Nonparametric estimation of mixing densities for discrete distributions (2006)

Roueff, François, Rydén, Tobias

By a mixture density is meant a density of the form $\pi_{\mu}(\cdot)=\int\pi_{\theta}(\cdot)\times\mu(d\theta)$, where $(\pi_{\theta})_{\theta\in\Theta}$ is a family of probability densities and...

Nonparametric estimation of mixing densities for discrete distributions (2005)

Roueff, François, Rydén, Tobias

By a mixture density is meant a density of the form πμ(⋅)=∫πθ(⋅)×μ(dθ), where (πθ)θ∈Θ is a family of probability densities and μ is a probability measure on Θ. We consider the...

Asymptotic properties of the maximum likelihood estimator in autoregressive models with Markov regime (2004)

Douc, Randal, Moulines, Éric, Rydén, Tobias

An autoregressive process with Markov regime is an autoregressive process for which the regression function at each time point is given by a nonobservable Markov chain. In this paper we consider the...

Linear Optimal Prediction and Innovations Representations of Hidden Markov Models (2003)

Andersson, Sofia, Rydén, Tobias, Johansson, Rolf

The topic of this paper is linear optimal prediction of hidden Markov models (HMMs) and innovations representations of HMMs. Our interest in these topics primarily arise from subspace estimation...

Hidden Markov and state space models: asymptotic analysis of exact and approximate methods for prediction, filtering, smoothing and statistical inference (2002)

Bickel, Peter, Ritov, Yaacov, Rydén, Tobias

State space models have long played an important role in signal processing. The Gaussian case can be treated algorithmically using the famous Kalman filter. Similarly since the 1970s there has been...

Statistical analysis of the influence of conspecifics on the dispersal of a soil collembola. (2002)

Bengtsson, Göran, Rydén, Tobias, Sjögren Ohrn, Maria, Wiktorsson, Magnus

The evidence for dispersal activity among soil-living invertebrates comes mainly from observations of their movement on artificial substrates or of colonisation of defaunated soils in the field. In...

Asymptotic normality of the maximum-likelihood estimator for general hidden Markov models (1998)

Bickel, Peter J., Ritov, Ya’acov, Rydén, Tobias

Hidden Markov models (HMMs) have during the last decade become a widespread tool for modeling sequences of dependent random variables. Inference for such models is usually based on the...

Reversible jump, birth-and-death and more general continuous time Markov chain Monte Carlo samplers

Olivier Cappé, Christian P. Robert, Tobias Rydén

Reversible jump methods are the most commonly used Markov chain Monte Carlo tool for exploring variable dimension statistical models. Recently, however, an alternative approach based on...

Stylized facts of daily return series and the hidden Markov model

Tobias Rydén, Timo Teräsvirta, Stefan Åsbrink

In two recent papers, Granger and Ding (1995a,b) considered long return series that are first differences of logarithmed price series or price indices. They established a set of temporal and...

Stylized Facts of Daily Return Series and the Hidden Markov Model

Rydén, Tobias, Teräsvirta, Timo, Åsbrink, Stefan

In two recent papers, Granger and Ding (1995a, b) considered long return series that are first differences of logarithmed price series or price indices. They established a set of temporal and...