21,519 research outputs found
On the history and use of some standard statistical models
This paper tries to tell the story of the general linear model, which saw the
light of day 200 years ago, and the assumptions underlying it. We distinguish
three principal stages (ignoring earlier more isolated instances). The model
was first proposed in the context of astronomical and geodesic observations,
where the main source of variation was observational error. This was the main
use of the model during the 19th century. In the 1920's it was developed in a
new direction by R.A. Fisher whose principal applications were in agriculture
and biology. Finally, beginning in the 1930's and 40's it became an important
tool for the social sciences. As new areas of applications were added, the
assumptions underlying the model tended to become more questionable, and the
resulting statistical techniques more prone to misuse.Comment: Published in at http://dx.doi.org/10.1214/193940307000000419 the IMS
Collections (http://www.imstat.org/publications/imscollections.htm) by the
Institute of Mathematical Statistics (http://www.imstat.org
Generalizations of the Familywise Error Rate
Consider the problem of simultaneously testing null hypotheses H_1,...,H_s.
The usual approach to dealing with the multiplicity problem is to restrict
attention to procedures that control the familywise error rate (FWER), the
probability of even one false rejection. In many applications, particularly if
s is large, one might be willing to tolerate more than one false rejection
provided the number of such cases is controlled, thereby increasing the ability
of the procedure to detect false null hypotheses. This suggests replacing
control of the FWER by controlling the probability of k or more false
rejections, which we call the k-FWER. We derive both single-step and stepdown
procedures that control the k-FWER, without making any assumptions concerning
the dependence structure of the p-values of the individual tests. In
particular, we derive a stepdown procedure that is quite simple to apply, and
prove that it cannot be improved without violation of control of the k-FWER. We
also consider the false discovery proportion (FDP) defined by the number of
false rejections divided by the total number of rejections (defined to be 0 if
there are no rejections). The false discovery rate proposed by Benjamini and
Hochberg [J. Roy. Statist. Soc. Ser. B 57 (1995) 289-300] controls E(FDP).
Here, we construct methods such that, for any \gamma and \alpha,
P{FDP>\gamma}\le\alpha. Two stepdown methods are proposed. The first holds
under mild conditions on the dependence structure of p-values, while the second
is more conservative but holds without any dependence assumptions.Comment: Published at http://dx.doi.org/10.1214/009053605000000084 in the
Annals of Statistics (http://www.imstat.org/aos/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Fluid thrust control system
A pure fluid thrust control system is described for a pump-fed, regeneratively cooled liquid propellant rocket engine. A proportional fluid amplifier and a bistable fluid amplifier control overshoot in the starting of the engine and take it to a predetermined thrust. An ejector type pump is provided in the line between the liquid hydrogen rocket nozzle heat exchanger and the turbine driving the fuel pump to aid in bringing the fluid at this point back into the regular system when it is not bypassed. The thrust control system is intended to function in environments too severe for mechanical controls
On Optimality of Stepdown and Stepup Multiple Test Procedures
Consider the multiple testing problem of testing k null hypotheses, where the
unknown family of distributions is assumed to satisfy a certain monotonicity
assumption. Attention is restricted to procedures that control the familywise
error rate in the strong sense and which satisfy a monotonicity condition.
Under these assumptions, we prove certain maximin optimality results for some
well-known stepdown and stepup procedures.Comment: Published at http://dx.doi.org/10.1214/009053605000000066 in the
Annals of Statistics (http://www.imstat.org/aos/) by the Institute of
Mathematical Statistics (http://www.imstat.org
A simple minimax estimator for quantum states
Quantum tomography requires repeated measurements of many copies of the
physical system, all prepared by a source in the unknown state. In the limit of
very many copies measured, the often-used maximum-likelihood (ML) method for
converting the gathered data into an estimate of the state works very well. For
smaller data sets, however, it often suffers from problems of rank deficiency
in the estimated state. For many systems of relevance for quantum information
processing, the preparation of a very large number of copies of the same
quantum state is still a technological challenge, which motivates us to look
for estimation strategies that perform well even when there is not much data.
In this article, we review the concept of minimax state estimation, and use
minimax ideas to construct a simple estimator for quantum states. We
demonstrate that, for the case of tomography of a single qubit, our estimator
significantly outperforms the ML estimator for small number of copies of the
state measured. Our estimator is always full-rank, and furthermore, has a
natural dependence on the number of copies measured, which is missing in the ML
estimator.Comment: 26 pages, 3 figures. v2 contains minor improvements to the text, and
an additional appendix on symmetric measurement
Stochastic demography and the neutral substitution rate in class-structured populations.
The neutral rate of allelic substitution is analyzed for a class-structured population subject to a stationary stochastic demographic process. The substitution rate is shown to be generally equal to the effective mutation rate, and under overlapping generations it can be expressed as the effective mutation rate in newborns when measured in units of average generation time. With uniform mutation rate across classes the substitution rate reduces to the mutation rate
A role for chromatin remodellers in replication of damaged DNA
In eukaryotic cells, replication past damaged sites in DNA is regulated by the ubiquitination of proliferating cell nuclear antigen (PCNA). Little is known about how this process is affected by chromatin structure. There are two isoforms of the Remodels the Structure of Chromatin (RSC) remodelling complex in yeast. We show that deletion of RSC2 results in a dramatic reduction in the level of PCNA ubiquitination after DNA-damaging treatments, whereas no such effect was observed after deletion of RSC1. Similarly, depletion of the BAF180 component of the corresponding PBAF (Polybromo BRG1 (Brahma-Related Gene 1) Associated Factor) complex in human cells led to a similar reduction in PCNA ubiquitination. Remarkably, we found that depletion of BAF180 resulted after UV-irradiation, in a reduction not only of ubiquitinated PCNA but also of chromatin-associated unmodified PCNA and Rad18 (the E3 ligase that ubiquitinates PCNA). This was accompanied by a modest decrease in fork progression. We propose a model to account for these findings that postulates an involvement of PBAF in repriming of replication downstream from replication forks blocked at sites of DNA damage. In support of this model, chromatin immunoprecipitation data show that the RSC complex in yeast is present in the vicinity of the replication forks, and by extrapolation, this is also likely to be the case for the PBAF complex in human cells
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