Forecasting the incidence of the disease in an area at a given time is a very interested study. It is important because it can be provide information early so that everything can be prepared to reduce the risks that may occur. One of the stochastic models that can explain the natural phenomena which occur in random in space and time is the point process. In this study, the incidence of the disease at any given time is considered as a temporal point process with inter event time is exponentially distributed. An interesting thing in this study is the conditional intensity of point process can be used to forecast the occurrence probability of exactly one event in one unit of time in the future. In this study, the parameters of conditional inte...
We summarize and discuss the current state of spatial point process theory and directions for future...
The thesis deals with point processes of objects with random lifetime. The form of the likelihood fu...
An extension of the stochastic susceptible-infectious-recovered (SIR) model is proposed in order to ...
We formulate the problem of on-line spatio-temporal disease surveillance in terms of predicting spat...
A novel point process model continuous in space-time is proposed for infectious disease data. Modell...
-Point Process is a stochastic model that can explain random natural phenomenon both in space and ti...
Study of inter event time is a part of temporal point process modeling. In this study, temporal poin...
We propose a class of Cox processes as models for the times of occurrence of cases of a disease, and...
Process Point is a stochastic model that can explain random natural phenomenon both in space and tim...
summary:A stochastic process cumulating random increments at random moments is studied. We model it ...
International audienceWe present a stochastic methodology to study the decay phase of an epidemic. I...
In recent decades there has been tremendous growth in new statistical methods and applications for m...
This paper deals with the development of statistical methodology for timely detection of incident di...
We consider a data set of locations where people in Central Bohemia have been infected by tick-borne...
Hazard rate estimation is one of the important topics in forecasting earthquake occurrence. Forecast...
We summarize and discuss the current state of spatial point process theory and directions for future...
The thesis deals with point processes of objects with random lifetime. The form of the likelihood fu...
An extension of the stochastic susceptible-infectious-recovered (SIR) model is proposed in order to ...
We formulate the problem of on-line spatio-temporal disease surveillance in terms of predicting spat...
A novel point process model continuous in space-time is proposed for infectious disease data. Modell...
-Point Process is a stochastic model that can explain random natural phenomenon both in space and ti...
Study of inter event time is a part of temporal point process modeling. In this study, temporal poin...
We propose a class of Cox processes as models for the times of occurrence of cases of a disease, and...
Process Point is a stochastic model that can explain random natural phenomenon both in space and tim...
summary:A stochastic process cumulating random increments at random moments is studied. We model it ...
International audienceWe present a stochastic methodology to study the decay phase of an epidemic. I...
In recent decades there has been tremendous growth in new statistical methods and applications for m...
This paper deals with the development of statistical methodology for timely detection of incident di...
We consider a data set of locations where people in Central Bohemia have been infected by tick-borne...
Hazard rate estimation is one of the important topics in forecasting earthquake occurrence. Forecast...
We summarize and discuss the current state of spatial point process theory and directions for future...
The thesis deals with point processes of objects with random lifetime. The form of the likelihood fu...
An extension of the stochastic susceptible-infectious-recovered (SIR) model is proposed in order to ...