# regression

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## regression

[re-gresh´un]
2. subsidence of symptoms or of a disease process.
3. in biology, the tendency in successive generations toward the mean.
4. an unconscious defense mechanism used to resolve conflict or frustration by returning to a behavior that was effective in earlier years. Some degree of regression frequently accompanies physical illness. Patients who are mentally ill may exhibit regression to an extreme degree, reverting all the way back to infantile behavior; this is called atavistic regression. adj., adj regres´sive.

## re·gres·sion

(rē-gresh'ŭn),
1. A subsidence of symptoms.
2. A relapse; a return of symptoms.
3. Any retrograde movement or action.
6. The distribution of one random variable given particular values of other variables relevant to it (for example, a formula for the distribution of weight as a function of height and chest circumference). The method was formulated by Galton in his study of quantitative genetics.
[L. regredior, pp. -gressus, to go back]

## regression

/re·gres·sion/ (re-gresh´un)
2. subsidence of symptoms or of a disease process.
3. in biology, the tendency in successive generations toward the mean.
4. defensive retreat to an earlier, often infantile, pattern of behavior or thought.
5. a functional relationship between a random variable and the corresponding values of one or more independent variables.regres´sive

## regression

(rĭ-grĕsh′ən)
n.
1. The process or an instance of regressing, as to a less perfect or less developed state.
2. Psychology Reversion to an earlier or less mature pattern of feeling or behavior.
3. Medicine Subsidence of the symptoms or process of a disease.
4. Statistics A technique for predicting the value of a dependent variable as a function of one or more independent variables in the presence of random error.

## regression

[rigresh′ən]
Etymology: L, regredi, to go back
1 a retreat or backward movement in conditions, signs, or symptoms.
3 a tendency in physical development to become more typical of the population than of the parents, such as a child who attains a height closer to the average than to that of tall or short parents. regress, v.

## regression

Any return to an original state. See Atavistic regression, Generalized additive logistic regression, Hypnotic age regression, Least-squares regression, Linear regression, Past life regression, Psychoregression Medtalk The subsiding of disease Sx or a return to a state of health Oncology A receding of CA Psychiatry A partial, symbolic, conscious, or unconscious desire to return–regress to a state of dependency, as in an infantile pattern of reacting or thinking, which occurs in normal sleep, play, physical illness, and in various mental disorders.

## re·gres·sion

(rĕ-gresh'ŭn)
1. A subsidence of symptoms.
2. A relapse; a return of symptoms.
3. Any retrograde movement or action.
5. The tendency of offspring of exceptional parents to possess characteristics closer to those of the general population.
7. The distribution of one random variable given particular values of other variables relevant to it (e.g., a formula for the distribution of weight as a function of height and chest circumference).
[L. re-gredior, pp. -gressus, to go back]

## regression

1. A psychoanalytic term implying a return to childish or a more primitive form of behaviour or thought, as from a genital to an oral stage.
2. A psychological term denoting a temporary falling back to a less mature form of thinking in the process of learning how to manage new complexity. Cognitive psychologists view such regression as a normal part of mental development.
3. A statistical term defining the relationship two variables such that a change in one (the independent variable) is always associated with a change in the average value of the other (the dependent variable).

## Regression

In psychology, a return to earlier, usually childish or infantile, patterns of thought or behavior.

## regression

term open to misinterpretation, in that it means attenuation and subsequent resolution of symptoms or exacerbation of the disease state

## re·gres·sion

(rĕ-gresh'ŭn)
1. Subsidence of symptoms.
2. Relapse; return of symptoms.
3. Any retrograde movement or action.
[L. re-gredior, pp. -gressus, to go back]

## regression

2. subsidence of clinical signs or of a disease process.
3. in biology, the tendency in successive generations toward the mean.
4. the relationship between pairs of random variables; the mean of one variable and its location is influenced by another variable.

regression analysis
see regression analysis.
regression coefficient
is the factor which determines the slope of a regression line; the greater the coefficient the steeper the line.
curvilinear regression
when the relationship between two variables is not linear.
linear regression
the relationship between two variables is a straight line.
References in periodicals archive ?
Once the prediction limits for each training data point are obtained, LS-SVM is utilized to establish two regression functions that model the relationship between the input data and its corresponding prediction limits.
The regression function results on the regional dummies suggest that a fixed-effects specification may have some merit.
For POS, NEG, NET, and SUM, table 4 reports the estimated slopes from the linear and piecewise linear regression functions.
The result from the simulation study showed that under the null hypothesis, the regression function in linear form are well approximated in all situation, especially for the large sample sizes.
The regression function was generated using a logarithmic link function, that is, m(x) = exp ([[beta].
Figure 6 shows the regression functions for M1 and F1 in the three experiments.
Pons (Institute of Agronomic Research, France) presents new mathematical results about statistical methods for the density and regression functions, which appear widely in the mathematical literature.
To assess the relative share of intra-inter specific competition between wheat and weeds, the following multiple linear regression functions were fitted between seed yield of individual wheat plant (w) and biomass of individual wheat plant (w) as dependent variable and density, leaf surface, dry weight of the leaf, relative leaf surface, total dry weight and total relative dry weight of weeds as independent variable to fit the best function and independent variable:
White, Halbert, "Using Least Squares to Approximate Unknown Regression Functions.
Algorithm for regression functions, Scientific Bulletin of "Politehnica" University of Bucharest, Series D, ISSN 1220-3041, tom XLVI--XLVII, p.
For testing, regression functions between the above-mentioned factors and the answers provided to specific questions have been used.

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