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Regression With Time Series Structure
Regression or regressions may refer to: Science * Marine regression, coastal advance due to falling sea level, the opposite of marine transgression * Regression (medicine), a characteristic of diseases to express lighter symptoms or less extent (mainly for tumors), without disappearing totally * Regression (psychology), a defensive reaction to some unaccepted impulses * Nodal regression, the movement of the nodes of an object in orbit, in the opposite direction to the motion of the object Statistics * Regression analysis, a statistical technique for estimating the relationships among variables. There are several types of regression: ** Linear regression ** Simple linear regression ** Logistic regression ** Nonlinear regression ** Nonparametric regression ** Robust regression ** Stepwise regression * Regression toward the mean, a common statistical phenomenon Computing * Software regression, the appearance of a bug which was absent in a previous revision ** Regression testing, a s ...
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Marine Regression
A marine regression is a geological process occurring when areas of submerged seafloor are exposed above the sea level. The opposite event, marine transgression, occurs when flooding from the sea covers previously-exposed land. Evidence of marine regressions and transgressions occurs throughout the fossil record, and the fluctuations are thought to have caused or contributed to several mass extinctions, such as the Permian-Triassic extinction event (250 million years ago) and Cretaceous–Paleogene extinction event (66 Ma). During the Permian-Triassic extinction, the largest extinction event in the Earth's history, the global sea level fell 250 m (820 ft). A major regression could itself cause marine organisms in shallow seas to go extinct, but mass extinctions tend to involve both terrestrial and aquatic species, and it is harder to see how a marine regression could cause widespread extinctions of land animals. Regressions are, therefore, seen as correlates or symptoms of major ...
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Stepwise Regression
In statistics, stepwise regression is a method of fitting regression models in which the choice of predictive variables is carried out by an automatic procedure. In each step, a variable is considered for addition to or subtraction from the set of explanatory variables based on some prespecified criterion. Usually, this takes the form of a forward, backward, or combined sequence of ''F''-tests or ''t''-tests. The frequent practice of fitting the final selected model followed by reporting estimates and confidence intervals without adjusting them to take the model building process into account has led to calls to stop using stepwise model building altogetherFlom, P. L. and Cassell, D. L. (2007) "Stopping stepwise: Why stepwise and similar selection methods are bad, and what you should use," NESUG 2007. or to at least make sure model uncertainty is correctly reflected.Chatfield, C. (1995) "Model uncertainty, data mining and statistical inference," J. R. Statist. Soc. A 158, Part 3, ...
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Regression (film)
''Regression'' is a 2015 psychological thriller horror mystery film directed and written by Alejandro Amenábar. The film stars Ethan Hawke and Emma Watson, with David Thewlis, Lothaire Bluteau, Dale Dickey, David Dencik, Peter MacNeill, Devon Bostick, and Aaron Ashmore in supporting roles. The film had its world premiere at the San Sebastián International Film Festival on September 18, 2015. It was released in the United States on October 9, 2015, by The Weinstein Company under the banner RADiUS-TWC. The film received mostly negative reviews from critics. Plot The film takes place in Minnesota, in 1990. Detective Bruce Kenner (Ethan Hawke) investigates the case of John Gray (David Dencik), who admits to sexually abusing his 17-year-old daughter Angela (Emma Watson) but has no recollection of the abuse. They seek the help of Professor Kenneth Raines (David Thewlis) to use recovered-memory therapy on John Gray to retrieve his memories, and come to suspect that their colleagu ...
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Infinite Regress
An infinite regress is an infinite series of entities governed by a recursive principle that determines how each entity in the series depends on or is produced by its predecessor. In the epistemic regress, for example, a belief is justified because it is based on another belief that is justified. But this other belief is itself in need of one more justified belief for itself to be justified and so on. An infinite regress argument is an argument against a theory based on the fact that this theory leads to an infinite regress. For such an argument to be successful, it has to demonstrate not just that the theory in question entails an infinite regress but also that this regress is ''vicious''. There are different ways in which a regress can be vicious. The most serious form of viciousness involves a contradiction in the form of ''metaphysical impossibility''. Other forms occur when the infinite regress is responsible for the theory in question being implausible or for its failure to ...
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Past Life Regression
Past life regression is a method that uses hypnosis to recover what practitioners believe are memories of past lives or incarnations. The practice is widely considered discredited and unscientific by medical practitioners, and experts generally regard claims of recovered memories of past lives as fantasies or delusions or a type of confabulation. Past-life regression is typically undertaken either in pursuit of a spiritual experience, or in a psychotherapeutic setting. Most advocates loosely adhere to beliefs about reincarnation, though religious traditions that incorporate reincarnation generally do not include the idea of repressed memories of past lives. The technique used during past-life regression involves the subject answering a series of questions while hypnotized to reveal identity and events of alleged past lives, a method similar to that used in recovered memory therapy and one that, similarly, often misrepresents memory as a faithful recording of previous events rather ...
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Age Regression In Therapy
Age regression in therapy is a psycho-therapeutic process that aims to facilitate access to childhood memories, thoughts, and feelings. Age regression can be induced by hypnotherapy, which is a process where patients move their focus to memories of an earlier stage of life in order to explore these memories or to access difficult aspects of their personality. Age regression has become controversial both inside and outside of the therapeutic community, with many cases involving alleged child abuse, alien abduction, rape, and other traumatic incidents subsequently being discredited. The notion of age regression is central to attachment therapy, whose proponents believe that a child who has missed out on their developmental stages can be made to experience those stages at a later age by a variety of techniques. Many of these techniques are intensely physical and confrontational, and include forced holding of eye contact, sometimes while being required to access traumatic memories ...
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Regression Testing
Regression testing (rarely, ''non-regression testing'') is re-running functional and non-functional tests to ensure that previously developed and tested software still performs as expected after a change. If not, that would be called a '' regression''. Changes that may require regression testing include bug fixes, software enhancements, configuration changes, and even substitution of electronic components. As regression test suites tend to grow with each found defect, test automation is frequently involved. Sometimes a change impact analysis is performed to determine an appropriate subset of tests (''non-regression analysis''). Background As software is updated or changed, or reused on a modified target, emergence of new faults and/or re-emergence of old faults is quite common. Sometimes re-emergence occurs because a fix gets lost through poor revision control practices (or simple human error in revision control). Often, a fix for a problem will be "fragile" in that it fi ...
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Software Regression
A software regression is a type of software bug where a feature that has worked before stops working. This may happen after changes are applied to the software's source code, including the addition of new features and bug fixes. They may also be introduced by changes to the environment in which the software is running, such as system upgrades, system patching or a change to daylight saving time. A software performance regression is a situation where the software still functions correctly, but performs more slowly or uses more memory or resources than before. Various types of software regressions have been identified in practice, including the following: * ''Local'' – a change introduces a new bug in the changed module or component. * ''Remote'' – a change in one part of the software breaks functionality in another module or component. * ''Unmasked'' – a change unmasks an already existing bug that had no effect before the change. Regressions are often caused by encompassed bu ...
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Regression Toward The Mean
In statistics, regression toward the mean (also called reversion to the mean, and reversion to mediocrity) is the fact that if one sample of a random variable is extreme, the next sampling of the same random variable is likely to be closer to its mean. Furthermore, when many random variables are sampled and the most extreme results are intentionally picked out, it refers to the fact that (in many cases) a second sampling of these picked-out variables will result in "less extreme" results, closer to the initial mean of all of the variables. Mathematically, the strength of this "regression" effect is dependent on whether or not all of the random variables are drawn from the same distribution, or if there are genuine differences in the underlying distributions for each random variable. In the first case, the "regression" effect is statistically likely to occur, but in the second case, it may occur less strongly or not at all. Regression toward the mean is thus a useful concept to ...
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Robust Regression
In robust statistics, robust regression seeks to overcome some limitations of traditional regression analysis. A regression analysis models the relationship between one or more independent variables and a dependent variable. Standard types of regression, such as ordinary least squares, have favourable properties if their underlying assumptions are true, but can give misleading results otherwise (i.e. are not robust to assumption violations). Robust regression methods are designed to limit the effect that violations of assumptions by the underlying data-generating process have on regression estimates. For example, least squares estimates for regression models are highly sensitive to outliers: an outlier with twice the error magnitude of a typical observation contributes four (two squared) times as much to the squared error loss, and therefore has more leverage over the regression estimates. The Huber loss function is a robust alternative to standard square error loss that reduces ...
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Regression (medicine)
Regression in medicine is a characteristic of diseases to decrease in severity and/or size. *Clinically, regression generally refers to lighter symptoms without completely disappearing. At a later point, symptoms may return. These symptoms are then called recidive. *In cancer, regression refers to a specific decrease in the size or extent of a tumour. In histopathology, ''histological regression'' is one or more areas within a tumor in which neoplastic cells have disappeared or decreased in number. In melanomas, this means complete or partial disappearance from areas of the dermis (and occasionally from the epidermis The epidermis is the outermost of the three layers that comprise the skin, the inner layers being the dermis and hypodermis. The epidermis layer provides a barrier to infection from environmental pathogens and regulates the amount of water rele ...), which have been replaced by fibrosis, accompanied by melanophages, new blood vessels, and a variable degree of i ...
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Nonparametric Regression
Nonparametric regression is a category of regression analysis in which the predictor does not take a predetermined form but is constructed according to information derived from the data. That is, no parametric form is assumed for the relationship between predictors and dependent variable. Nonparametric regression requires larger sample sizes than regression based on parametric models because the data must supply the model structure as well as the model estimates. Definition In nonparametric regression, we have random variables X and Y and assume the following relationship: : \mathbb \mid X=x= m(x), where m(x) is some deterministic function. Linear regression is a restricted case of nonparametric regression where m(x) is assumed to be affine. Some authors use a slightly stronger assumption of additive noise: : Y = m(X) + U, where the random variable U is the `noise term', with mean 0. Without the assumption that m belongs to a specific parametric family of functions it is impo ...
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