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Calibration diagnostics for point process models via the probability integral transform
Calibration diagnostics point process models probability integral transform
2013/6/14
We propose the use of the probability integral transform (PIT) for model validation in point process models. The simple PIT diagnostics assess the calibration of the model and can detect inconsistenci...
Diagnostics for Respondent-driven Sampling
diagnostics exploratory data analysis hard-to-reachpopulations HIV/AIDS link-tracingsampling non-ignorable design,respondent-driven sampling social networks survey sampling
2012/11/23
Respondent-driven sampling (RDS) is a widely used method for sampling from hard-to-reach human populations, especially groups most at-risk for HIV/AIDS. Data are collected through a peer-referral proc...
An asymptotic representation of Bahadur type of the
difference of M-estimators &l-fl$-lv'), i-e. of the difference of
mtimators of regression coefficients for the full data set and for the set
from...
Bayesian Model Diagnostics Based on Artificial Autoregressive Errors
Allometry Asymptotic normality Autocorrelation Hierarchical models Response times
2009/9/22
In this article I develop a simple and eective device for ascertaining the quality
of the modeling choices and detecting lack-of-fit. I specify an articial autoregres-
sive structure (AAR) in the pr...
Regression Diagnostics in an Autocorrelated Model
Regression Diagnostics an Autocorrelated Model
2009/9/17
Regression Diagnostics in an Autocorrelated Model。
Graphical display in outlier diagnostics：adequacy and robustness
Masking outlier robust diagnostics robust residuals swamping
2009/2/23
Outlier robust diagnostics (graphically) using Robustly Studentized Robust Residuals (RSRR) and
Partial Robustly Studentized Robust Residuals (PRSRR) are established. One problem with some
robust re...
Influence diagnostics in exponentiated-Weibull regression models with censored data
Exponentiated-Weibull distribution censored data local influence influence diagnostic survival data
2009/2/23
Diagnostic methods have been an important tool in regression analysis to detect anomalies, such
as departures from the error assumptions and the presence of outliers and influential observations with...