Add to ORKGA regression may be constant for small values of the independent variable (for example time), but then a monotonic increase starts. Such an “outbreak” regression is of interest for example in the study of the outbreak of an epidemic disease. We give the least square estimators for this outbreak regression without assumption of a parametric regression function. It is shown that the least squares estimators are also the maximum likelihood estimators for distributions in the regular exponential family such as the Gaussian or Poisson distribution. The approach is thus semiparametric. The method is applied to Swedish data on influenza, and the properties are demonstrated by a simulation study. The consistency of the estimator is proved.Swedish E...
Infectious disease often occurs in small, independent outbreaks in populations with varying characte...
<div><p>This paper proposes a novel approach that uses meteorological information to predict the inc...
This paper proposes a novel approach that uses meteorological information to predict the incidence o...
A regression may be constant for small values of the independent variable (for example time), but th...
The detection of a change from a constant level to a monotonically increasing (or decreasing) regres...
The detection of a change from a constant level to a monotonically increasing (or decreasing) regres...
Robust regression is of interest in many problems where assumptions of a parametric function may be ...
Robust regression is of interest in many problems where assumptions of a parametric function may be ...
We describe and discuss statistical models of Swedish influenza data, with special focus on aspects ...
On-line monitoring is needed to detect outbreaks of diseases like influenza. Surveillance is also ne...
On-line monitoring is needed to detect outbreaks of diseases like influenza. Surveillance is also ne...
<p>(A and B) The least squares error (LSE) (A) and <i>R</i><sub>0</sub> (B) of the best-fit model un...
A statistical surveillance system gives a signal as soon as data give enough evidence of an importan...
A statistical surveillance system gives a signal as soon as data give enough evidence of an importan...
SEIRS and SVEIRS epidemic models are considered here to capture the main characteristic of transmiss...
Infectious disease often occurs in small, independent outbreaks in populations with varying characte...
<div><p>This paper proposes a novel approach that uses meteorological information to predict the inc...
This paper proposes a novel approach that uses meteorological information to predict the incidence o...
A regression may be constant for small values of the independent variable (for example time), but th...
The detection of a change from a constant level to a monotonically increasing (or decreasing) regres...
The detection of a change from a constant level to a monotonically increasing (or decreasing) regres...
Robust regression is of interest in many problems where assumptions of a parametric function may be ...
Robust regression is of interest in many problems where assumptions of a parametric function may be ...
We describe and discuss statistical models of Swedish influenza data, with special focus on aspects ...
On-line monitoring is needed to detect outbreaks of diseases like influenza. Surveillance is also ne...
On-line monitoring is needed to detect outbreaks of diseases like influenza. Surveillance is also ne...
<p>(A and B) The least squares error (LSE) (A) and <i>R</i><sub>0</sub> (B) of the best-fit model un...
A statistical surveillance system gives a signal as soon as data give enough evidence of an importan...
A statistical surveillance system gives a signal as soon as data give enough evidence of an importan...
SEIRS and SVEIRS epidemic models are considered here to capture the main characteristic of transmiss...
Infectious disease often occurs in small, independent outbreaks in populations with varying characte...
<div><p>This paper proposes a novel approach that uses meteorological information to predict the inc...
This paper proposes a novel approach that uses meteorological information to predict the incidence o...