Results 261 to 270 of about 46,298 (299)

Nonparametric Hypothesis Testing

1993
The present chapter takes the same starting point as Chapter IV, although rather than estimation in the multiplicative intensity model, we now consider hypothesis testing. The general remarks made in the Introduction to Chapter IV concerning the underlying model and the specification of the counting process under aggregation of censored, truncated, or ...
Per Kragh Andersen, Ørnulf Borgan, Richard D. Gill, Niels Keiding   +3 more
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Bayesian nonparametric hypothesis testing for longitudinal data analysis

Computational Statistics & Data Analysis, 2023
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Luz Adriana Pereira, Luis Gutiérrez, Daniel Taylor-Rodríguez, Ramsés H. Mena   +3 more
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Inferential Statistics III: Nonparametric Hypothesis Testing

2019
Andrew P. King, Robert J. Eckersley
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Nonparametric hypothesis testing

2011
The log-rank test is arguably the most widely used test in survival analysis. In this brief Chapter, we explain the idea of the log-rank test and how it translates to competing risks. The key issue is that the log-rank test compares hazards and may consequently be used to compare cause-specific hazards, too. As we have seen earlier, differences between
Jan Beyersmann, Martin Schumacher, Arthur Allignol   +2 more
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Nonparametric hypothesis testing in clustered survival model

Communications in Statistics - Simulation and Computation, 2017
A nonparametric test for the presence of clustering in survival data is proposed. Assuming a model that incorporates the clustering effect into the Cox Proportional Hazards model, simulation studie...
John de Guzman Eustaquio, Erniel B. Barrios   +1 more
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Nonparametric Hypothesis Testing for a Spatial Signal

Journal of the American Statistical Association, 2002
Summary form only given. Nonparametric hypothesis testing for a spatial signal can involve a large number of hypotheses. For instance, two satellite images of the same scene, taken before and after an event, could be used to test a hypothesis that the event has no environmental impact.
Shen, Xiaotong, Huang, Hsincheng, Cressie, Noel A   +2 more
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Bayesian nonparametric hypothesis testing methods on multiple comparisons

Computational Statistics
Zhuanzhuan Ma
exaly   +2 more sources

Nonparametric Hypothesis Testing

2014
A novel presentation of rank and permutation tests, with accessible guidance to applications in R. Nonparametric testing problems are frequently encountered in many scientific disciplines, such as engineering, medicine and the social sciences. This book summarizes traditional rank techniques and more recent developments in permutation testing as robust
BONNINI, Stefano, CORAIN, Livio, MAROZZI, Marco, SALMASO, Luigi   +3 more
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Nonparametric Hypothesis Tests

2016
The parametric methods of the previous chapter required data measured at the interval or ratio levels and which is normally distributed. Business data are not always at these levels of measurement. Market research regularly produces data at the nominal (e.g. “agree” versus “disagree” with a proposition about a product) and ordinal (e.g.
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Hypothesis Testing and Nonparametric Test

2018
It is often required to make some inferences about some parameter of the population on the basis of available data. Such inferences are very important in hydrology and hydroclimatology where the available data is generally limited. This is done through hypothesis testing.
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