Results 291 to 300 of about 22,265,852 (345)

Null or minimal models

1994
Abstract The problem with models in phylogenetic inference is one of regress or circularity. Sound models demand either some knowledge of phylogeny, or assumptions about it. If knowledge is claimed, how was that knowledge gained? If assumptions are held to be merely provisional or approximate, how will they be tested by phylogenies that ...
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Toward ecologically explicit null models of nestedness

Oecologia, 2007
A community is "nested" when species assemblages in less rich sites form nonrandom subsets of those at richer sites. Conventional null models used to test for statistically nonrandom nestedness are under- or over-restrictive because they do not sufficiently isolate ecological processes of interest, which hinders ecological inference. We propose a class
Jeffrey E, Moore, Robert K, Swihart
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AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models

International Conference on Learning Representations
Large language models (LLMs) often exhibit hallucinations due to incorrect or outdated knowledge. Hence, model editing methods have emerged to enable targeted knowledge updates. To achieve this, a prevailing paradigm is the locating-then-editing approach,
Junfeng Fang, Houcheng Jiang, Kun Wang, Yunshan Ma, Xiang Wang, Xiangnan He, Tat-Seng Chua   +6 more
semanticscholar   +1 more source

Null Hypothesis Models in Legislative Studies

The Journal of Politics, 1983
P olitical scientists often refer to the existence of "coalitions" in Congress, but remarkably little effort has been made to discover the reasons why the votes of various congressmen might be similar. It may be that coalition formation-the explicit coordination of voting decisions-has indeed occurred.
Thomas H. Hammond, Jane M. Fraser
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SWAP ALGORITHMS IN NULL MODEL ANALYSIS

Ecology, 2003
Null model analysis is an important research tool in community ecology (Gotelli 2001). Researchers compare community data with randomized data to ask how communities would appear if they were structured only by stochastic factors (Gotelli and Graves 1996).
Nicholas J. Gotelli, Gary L. Entsminger
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Random Graphs as Null Models

2016
In the last chapter, a qualitative comparison of various real-world structures with classic random graph models revealed that complex networks are non-random in many aspects. This chapter focuses on the question of how to quantify the statistical significance of an observed network structure with respect to a given random graph model.
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Null models in ecology

Choice Reviews Online, 1997
Kimberly A. With, Nicholas J. Gotelli, Gary R. Graves   +2 more
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Null Models in Cluster Validation

1996
A brief overview is given of the problem of validation in classification studies. Attention is concentrated on the specification of appropriate null models for data, with respect to which one may assess some cluster structure that has been obtained as the output of a clustering algorithm.
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The use and limitations of null-model-based hypothesis testing

, 2020
Mingjun Zhang
semanticscholar   +1 more source

Research frontiers in null model analysis

Global Ecology and Biogeography, 2001
AbstractNull models are pattern‐generating models that deliberately exclude a mechanism of interest, and allow for randomization tests of ecological and biogeographic data. Although they have had a controversial history, null models are widely used as statistical tools by ecologists and biogeographers.
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