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329
Tamoxifen for prevention of breast cancer: report of the National Surgical Adjuvant Breast and Bowel Project P1 study
 J. Natl. Cancer Inst
, 1998
"... Background: The finding of a decrease in contralateral breast cancer incidence following tamoxifen administration for adjuvant therapy led to the concept that the drug might play a role in breast cancer prevention. To test this hypothesis, ..."
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Cited by 90 (0 self)
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Background: The finding of a decrease in contralateral breast cancer incidence following tamoxifen administration for adjuvant therapy led to the concept that the drug might play a role in breast cancer prevention. To test this hypothesis,
Bayesian wavelet regression on curves with application to a spectroscopic calibration problem
 Journal of the American Statistical Association
, 2001
"... Motivated by calibration problems in nearinfrared (N IR) spectroscopy, we consider the linear regression setting in which the many predictor variables arise from sampling an essentially continuous curve at equally spaced points and there may be multiple predictands. We tackle this regression proble ..."
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Cited by 46 (5 self)
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Motivated by calibration problems in nearinfrared (N IR) spectroscopy, we consider the linear regression setting in which the many predictor variables arise from sampling an essentially continuous curve at equally spaced points and there may be multiple predictands. We tackle this regression problem by calculating the wavelet transforms of the discretized curves, then applying a Bayesian variable selection method using mixture priors to the multivariate regression of predictands on wavelet coef � cients. For prediction purposes, we average over a set of likely models. Applied to a particular problem in N IR spectroscopy, this approach was able to � nd subsets of the wavelet coef � cients with overall better predictive performance than the more usual approaches. In the application, the available predictors are measurements of the N IR re � ectance spectrum of biscuit dough pieces at 256 equally spaced wavelengths. The aim is to predict the composition (i.e., the fat, � our, sugar, and water content) of the dough pieces using the spectral variables. Thus we have a multivariate regression of four predictands on 256 predictors with quite high intercorrelation among the predictors. A training set of 39 samples is available to � t this regression. Applying a wavelet transform replaces the 256 measurements on each spectrum with 256 wavelet coef � cients that carry the same information. The variable selection method could use subsets of these coef � cients that gave good predictions for all four compositional variables on a separate test set of samples. Selecting in the wavelet domain rather than from the original spectral variables is appealing in this application, because a single wavelet coef � cient can carry information from a band of wavelengths in the original spectrum. This band can be narrow or wide, depending on the scale of the wavelet selected.
Temporal pitch in electric hearing
 Hear Res
"... Both place and temporal codes in the peripheral auditory system contain pitch information, however, their actual use by the brain is unclear. Here pitch data are reported from users of the cochlear implant, which provides the ability to change the temporal code independently from the place code. Wit ..."
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Cited by 16 (4 self)
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Both place and temporal codes in the peripheral auditory system contain pitch information, however, their actual use by the brain is unclear. Here pitch data are reported from users of the cochlear implant, which provides the ability to change the temporal code independently from the place code. With fixed electrode stimulation, both frequency discrimination and pitch estimate data show that the cochlear implant users can only discern differences in pitch for frequencies up to about 300 Hz. An integration model can predict pitch estimation from frequency discrimination, reinforcing Fechner’s hypothesis relating sensation magnitude to stimulus discriminability. The present results suggest that 300 Hz is the upper boundary of the temporal code and that the absolute place information should be included in the present pitch models. They further suggest that future cochlear implants need to increase the number of independent electrodes to restore normal pitch range and resolution.
Soil erosion in the West African Sahel: a review and an application of a “local political ecology” approach
 in South West Niger. Global Environmental Change
, 2001
"... A review of soil erosion research in the West African Sahel "nds that there are insu$cient data on which to base policy. This is largely because of the di$culties of measuring erosion and the other components of ‘soil lifea, and because of the highly spatially and temporarily variable natural a ..."
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Cited by 13 (1 self)
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A review of soil erosion research in the West African Sahel "nds that there are insu$cient data on which to base policy. This is largely because of the di$culties of measuring erosion and the other components of ‘soil lifea, and because of the highly spatially and temporarily variable natural and social environment of the Sahel. However, a ‘local political ecologya of soil erosion and new methodologies o!er some hope of overcoming these problems. Nonetheless, a major knowledge gap will remain, about how rates of erosion are accommodated and appraised within very variable social and economic conditions. An example from recent "eld work in Niger shows that erosion is correlated with factors such as male migration, suggesting, in this case, that households with access to nonfarm income adopt a riskavoidance strategy in which soil erosion is accelerated incidentally. It is concluded that there needs to be more research into the relations between erosion and socioeconomic factors, and clearer thinking about the meaning of sustainability as it refers to soil erosion in the Sahel. ( 2001 Elsevier Science Ltd. All rights reserved.
Model Selection
 In The Handbook Of Financial Time Series
, 2008
"... Model selection has become an ubiquitous statistical activity in the last decades, none the least due to the computational ease with which many statistical models can be fitted to data with the help of modern computing equipment. In this article we provide an introduction to the statistical aspect ..."
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Cited by 14 (0 self)
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Model selection has become an ubiquitous statistical activity in the last decades, none the least due to the computational ease with which many statistical models can be fitted to data with the help of modern computing equipment. In this article we provide an introduction to the statistical aspects and implications of model selection and we review the relevant literature. 1.1 A General Formulation When modeling data Y, a researcher often has available a menu of competing candidate models which could be used to describe the data. Let M denote the collection of these candidate models. Each model M, i.e., each element of M, can – from a mathematical point of view – be viewed as a collection of probability distributions for Y implied by the model. That is, M is given by M = {Pη: η ∈ H}, where Pη denotes a probability distribution for Y and H represents the ‘parameter ’ space (which can be different across different models M). The ‘parameter ’ space H need not be finitedimensional. Often, the ‘parameter ’ η will be partitioned into (η1, η2) where η1 is a finitedimensional parameter whereas η2 is infinitedimensional. In case the parameterization is identified, i.e., the map η → Pη is injective on H, we will often not distinguish between M and H and will use them synonymously. The model selection problem is now to select – based on the data Y – a model M ̂ = M̂(Y) in M such that M ̂ is a ‘good ’ model for the data Y. Of course, the sense, in which the selected model should be a ‘good ’ model, needs to be made precise and is a crucial point in the analysis. This is particularly important if – as is usually the case – selecting the model M ̂ is not the final
1 Bayesian statistics and the agrofood production chain
"... The essence of the Bayesian approach to inference is that all uncertainly is expressed through the specification of probability distributions. Its use is particularly advantageous in situations where uncertainties of various kinds have to be combined, in situations where the desired end is a probabi ..."
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The essence of the Bayesian approach to inference is that all uncertainly is expressed through the specification of probability distributions. Its use is particularly advantageous in situations where uncertainties of various kinds have to be combined, in situations where the desired end is a probability statement about a hypothesis, in problems that involve making a decision, and in the modelling of complex systems. Opportunities of all these types exist in the agrofood production chain.
Thermal Control..............................................................................
"... Surface...........................................................................................................................19 ..."
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Surface...........................................................................................................................19
Abstract NIR and mass spectra classification: Bayesian methods for waveletbased feature selection
, 2005
"... Here we focus on classification problems that involve functional predictors, specifically spectral data. One of our practical contexts involves the classification of three wheat varieties based on 100 near infrared absorbances. The dataset consists of a total 117 samples of wheat collected during a ..."
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Here we focus on classification problems that involve functional predictors, specifically spectral data. One of our practical contexts involves the classification of three wheat varieties based on 100 near infrared absorbances. The dataset consists of a total 117 samples of wheat collected during a study that aimed at exploring the possibility of using NIR spectra to assign unknown samples to the correct variety. In another example we look at serum spectra from 162 ovarian cancer and 91 control subjects generated through surface enhanced laser desorption ionization timetoflight mass spectrometry (SELDITOF). We employ wavelet transforms as a tool for dimension reduction and noise removal, reducing spectra to wavelet components. We then use probit models and Bayesian methods that allow the simultaneous classification of the samples as well as the selection of the discriminating features of the spectra. In both examples our method is able to find very small sets of features that lead to good classification results.
Body Movement and Presence 1 The Influence of Body Movement on Subjective Presence in Virtual Environments
"... This paper describes an experiment to assess the influence of body movements on presence in a virtual environment. Twenty subjects were required to walk through a virtual field of trees and count the number of trees with diseased leaves. A 2? 2 betweensubjects design was used to assess the influenc ..."
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This paper describes an experiment to assess the influence of body movements on presence in a virtual environment. Twenty subjects were required to walk through a virtual field of trees and count the number of trees with diseased leaves. A 2? 2 betweensubjects design was used to assess the influence of two factors on presence. One factor was tree height variation, and a second factor was the complexity of the task. The field with greater variation in tree height required subjects to bend down and look up more than those in the lower variation tree height field. Those with the higher complexity task were told to remember the distribution of diseased trees in the field, as well as to count them. The results showed a significant positive association between reported presence and the amount of body movement, in particular head yaw, and the extent to which subjects bent down and stood up. There was also a strong interaction effect between the task complexity and gender, with females in the group with the more complex task reporting a much lower sense of presence than in the simpler task.
London, WC1E 6BT United Kingdom
"... Elastic scattering spectroscopy for detection of cancer risk in Barrett’s esophagus: experimental and clinical validation of error removal by orthogonal subtraction for increasing accuracy ..."
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Elastic scattering spectroscopy for detection of cancer risk in Barrett’s esophagus: experimental and clinical validation of error removal by orthogonal subtraction for increasing accuracy
Results 1  10
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329