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Nuisance variable

In the theory of stochastic processes in probability theory and statistics, a nuisance variable is a random variable that is fundamental to the… 
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Related topics

Related topics

2 relations
Bayesian networkStochastic process

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
Road Traffic Noise Forecast (RTNF) in the Process of Creating Urban Space - Case Study of Poland
Road traffic noise is one of the main nuisance factors in a city. This creates the necessity of determining and monitoring not… 
2015
2015
Blocking benefits: Including nuisance factors during experimentation
2014
2014
Watch-List Screening Using Ensembles Based on Multiple Face Representations
Still-to-video face recognition (FR) is an important function in watch list screening, where faces captured over a network of… 
2014
2014
The measurement invariance and measurement equivalence of the sources of work stress inventory (SWSI) across gender groups in South Africa
The primary goal of an organisation, in a capitalistic system, is the maximisation of profit. The task of the human resource… 
2014
2014
Design of RNA Sequencing Experiments
This chapter presents strategies for the design of RNA sequencing (RNA-seq) experiments aimed at identifying differentially… 
2013
2013
On the Design and Analysis of Multiple View Descriptors
We propose an extension of popular descriptors based on gradient orientation histograms (HOG, computed in a single image) to… 
2010
2010
Embedded Imagers: Detecting, Localizing, and Recognizing Objects and Events in Natural Habitats
Imaging sensors, or “imagers,” embedded in the natural environment enable remote collection of large quantities of data, thus… 
2007
2007
Delineamento de experimentos em genética genômica
Genetica genomica e um termo utilizado para representar o estudo de processos geneticos controladores de caracteres fenotipicos… 
2006
2006
Analysis of Mass Spectrometry Data Using Bayesian Wavelet-Based Functional Mixed Models
In this chapter, we demonstrate how to analyze MALDI-TOF/SELDITOF mass spectrometry data using the wavelet-based functional mixed… 
2006
2006
Using Bayesian inference for parameter estimation when the system response and experimental conditions are measured with error and some variables are considered as nuisance variables
Parameter estimation is generally based upon the maximum likelihood approach and often involves regularization. Typically it is… 
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