prior information
Shrinkage estimation of the slope parameters of two parallel regression lines under uncertain prior information
... In the next section, we introduce the parallelism model and define the null hypothesis to present the uncertain prior information. Section 3 defines three different estimators of the vector of the slope ...
17
Test of hypotheses for linear regression models with non-sample prior information
... Classical inferences about population parameters are usually drawn from the sample data alone. This applies to methods used in parameter estimation and hypothesis testing. Inferences about population parameters could be ...
207
Estimation of the intercept parameter for linear regression model with uncertain non-sample prior information
... A large number of studies have been conducted in the area of the ‘improved’ estimation following the seminal work of Bancroft (1944) and later Han and Bancroft (1968). They developed the preliminary test estimator that ...
18
Estimation of the parameters of two parallel regression lines under uncertain prior information
... when it is apriori suspected that the slopes of the two regression lines are equal, but not sure. In this paper we define and investigate three different estimators of the intercept and the slope parameters of two linear ...
16
Testing equality of two intercepts for the parallel regression model with non-sample prior information
... It is well known that, for any linear regression model, the inference on the intercept parameter depends on the value of the slope param- eter. Thus the non-sample prior information on the value of the ...
17
Test of hypotheses for linear regression models with non-sample prior information
... Classical inferences about population parameters are usually drawn from the sample data alone. This applies to methods used in parameter estimation and hypothesis testing. Inferences about population parameters could be ...
12
Estimation of the slope parameter for linear regression model with uncertain prior information
... uncertain prior information on the value of the slope is ...non-sample information regarding the value of the slope is close to its true value, the shrinkage estimator over performs the rest of the ...
21
Incorporation of genuine prior information in cost-effectiveness analysis of clinical trial data
... incorporate prior information in a cost-effectiveness analysis is a positive benefit of the Bayesian approach to statistical ...available information in addition to the clinical trial data, and hence ...
10
Improving statistical inference with uncertain non-sample prior information
... and prior distribution of the model ...non-sample prior information (NSPI) on the value of model parameters has been introduced to `improve' the quality of statistical ...additional ...
11
Multi-electrode stimulation and measurement patterns versus prior information of fast 3D EIT
... Electrical Impedance Tomography is an inverse problem, and thus in order to achieve meaningful results, the regularisation process should couple the stimulation and measurement strategies with prior ...
130
Distributed Estimation Based on Prior Information
... complete prior information, it can be seen from Table 1, that iteration time of the basic Bayesian-based FB KF, though it is very much optimal in nature due to its structure than the regular KF, is taking ...
34
Joint optimization of MIMO radar waveform and biased estimator with prior information in the presence of clutter
... any prior informa- tion. In fact, some prior information may be available in many array signal processing fields (see, ...and prior information are ...
13
A novel technique to incorporate structural prior information into multi-modal tomographic reconstruction
... There has been a rapid expansion of multi-modal imaging techniques in tomography. In biomedical imaging, patients are now regularly imaged using both single photon emission computed tomography (SPECT) and x-ray computed ...
18
Measuring the effect of observations using the posterior and intrinsic Bayes factors with vague prior information
... The main objective of this paper is to develop diagnostic measures for model checking and also model selection using the posterior and the intrinsic Bayes factor when the prior informati[r] ...
22
Estimation of the reciprocal of the mean of the Inverse Gaussian distribution with prior information
... little information about the parameter available from the sample and if there is any prior estimate for the parameter, the shrinkage method can be useful, see (Pandey, ...the prior point estimate λ 0 ...
16
Knowledge Matters: Importance of Prior Information for Optimization
... whole information about the input is given, but it is perfectly ...the information about the input image patch, but spread out in a kind of non-parametric and non-informative (not disentangled) way, like a ...
32
Constructing informative Bayesian map priors: A multi-objective optimisation approach applied to indoor occupancy grid mapping
... using prior information to improve the performance of robotics systems has been suggested for a number of systems that operate in real-world, challenging ...2015). Prior knowledge can be incorporated ...
32
Bayesian value-of-infomation analysis: an application to a policy model of Alzheimer's disease
... of prior information surrounding model inputs in the probabilistic model is summarized in Table ...The prior mean health state utility for each state in the model was characterized as normally ...
18
“Philosophical Treatises on Life and Death”:Newspaper Coverage of a Controversial Brain Death Case
... the information of ordered p-values to assign particular sizes to the corresponding individual ...assumed prior information. Although the procedures utilize prior information to choose ...
106
Informative Bayesian Modeling With Applications to Media Data
... to information integration (meta-analysis, Sutton and Abrams (2001), Trikalinos et ...call information reweighted priors ...heterogeneity, prior information (that we will return to), and allow ...
103