Results 11 to 20 of about 119 (60)
Sequential risk‐efficient estimation of the parameter in the uniform density
International Journal of Mathematics and Mathematical Sciences, Volume 23, Issue 6, Page 415-423, 2000., 2000 We develop a risk‐efficient sequential procedure for estimating the parameter θ of the uniform density on (0, θ). We give explicit expressions for the distribution of the stopping time and derive its expectation and variance. We also tabulate the values of the expected stopping time and its standard deviation for some selected values of the parameter ...
Z. Govindarajulu
wiley +1 more source
Sequential point and interval estimation of scale parameter of exponential distribution
International Journal of Mathematics and Mathematical Sciences, Volume 18, Issue 2, Page 383-390, 1995., 1995 Sequential fixed‐width confidence intervals are obtained for the scale parameter σ when the location parameter θ of the negative exponential distribution is unknown. Exact expressions for the stopping time and the confidence coefficient associated with the sequential fixed‐width interval are derived.
Z. Govindarajulu
wiley +1 more source
Bayesian sequential estimation of the reliability of a parallel-series system
, 2012 We give a risk-averse solution to the problem of estimating the reliability of a parallel-series system. We adopt a beta-binomial model for components reliabilities, and assume that the total sample size for the experience is fixed.
Benkamra +12 more
core +1 more source
Research in StatisticsA sequential procedure is developed to construct a fixed accuracy confidence interval (CI) of the common unknown variance of the random observations, where the observations arise from a first-order stationary autoregressive (AR(1)) process with a ...
Rahul Bhattacharya +3 more
doaj +1 more source
Analysis of Testing-Based Forward Model Selection [PDF]
, 2020 This paper introduces and analyzes a procedure called Testing-based forward model selection (TBFMS) in linear regression problems. This procedure inductively selects covariates that add predictive power into a working statistical model before estimating ...
Kozbur, Damian
core +1 more source
Sharp failure rates for the bootstrap particle filter in high dimensions
, 2008 We prove that the maximum of the sample importance weights in a high-dimensional Gaussian particle filter converges to unity unless the ensemble size grows exponentially in the system dimension.
Bengtsson, Thomas, Bickel, Peter, Li, Bo
core +1 more source
Journal of Causal InferenceTime-dependent coarse structural nested mean models (coarse SNMMs) were developed to estimate treatment effects from longitudinal observational data. Coarse SNMMs estimate the combined effect of multiple treatment dosages and are thus useful to estimate ...
Lok Judith J.
doaj +1 more source
A Quasi-Bayesian Perspective to Online Clustering [PDF]
, 2018 When faced with high frequency streams of data, clustering raises theoretical and algorithmic pitfalls. We introduce a new and adaptive online clustering algorithm relying on a quasi-Bayesian approach, with a dynamic (i.e., time-dependent) estimation of ...
Guedj, Benjamin +2 more
core +5 more sources
Recursive Parameter Estimation: Convergence
, 2007 We consider estimation procedures which are recursive in the sense that each successive estimator is obtained from the previous one by a simple adjustment.
Sharia, Teo
core +2 more sources
Smoothing and filtering with a class of outer measures [PDF]
, 2018 Filtering and smoothing with a generalised representation of uncertainty is considered. Here, uncertainty is represented using a class of outer measures.
Bishop, Adrian N., Houssineau, Jeremie
core +1 more source