A Stochastic error term is a term that is added to a regression equation to introduce all of the variation in Y that cannot be explained by the included Xs. It is, in effect, a symbol of the econometrician's ignorance or inability to model all the movements of the dependent variable.
In a statistical model, variations in the dependent variable can be attributed to independent variables. However, there is a random element that is not accounted for and this is the stochastic error.
Regression analysis is based on the assumption that the dependent variable is distributed according some function of the independent variables together with independent identically distributed random errors. If the error terms were not stochastic then some of the properties of the regression analysis are not valid.
The definition to the term "Stochastic Process" is: A statistical process involving a number of random variables depending on a number variable. Which in most cases, is time.
Mathematical model is exact in nature.it has Beta zero and Beta one and no stochastic or disturbance variables. Econometric model represents omitted variable, error in measurement and stochastic variables.
A beta error is another term for a type II error, an instance of accepting the null hypothesis when the null hypothesis is false.
A stochastic error indicates an error that is random between measurements. Stochastics typically occur through the sum of many random errors.
In a statistical model, variations in the dependent variable can be attributed to independent variables. However, there is a random element that is not accounted for and this is the stochastic error.
Regression analysis is based on the assumption that the dependent variable is distributed according some function of the independent variables together with independent identically distributed random errors. If the error terms were not stochastic then some of the properties of the regression analysis are not valid.
You can thank Kac and Nelson for the association of stochastic phenomena with probability and probabilistic events. There's a good Wikipedia page explaining in better detail.
the residual is the difference between the observed Y and the estimated regression line(Y), while the error term is the difference between the observed Y and the true regression equation (the expected value of Y). Error term is theoretical concept that can never be observed, but the residual is a real-world value that is calculated for each observation every time a regression is run. The reidual can be thought of as an estimate of the error term, and e could have been denoted as ^e.
The definition to the term "Stochastic Process" is: A statistical process involving a number of random variables depending on a number variable. Which in most cases, is time.
A stochastic disturbance term is a random variable included in a statistical model to account for unexplained variability or uncertainty in the data. It represents the effects of unobserved factors that are not explicitly modeled but can influence the outcome of an analysis. By incorporating this term, the model can better capture the randomness or unpredictability in the data.
Mathematical model is exact in nature.it has Beta zero and Beta one and no stochastic or disturbance variables. Econometric model represents omitted variable, error in measurement and stochastic variables.
Stochastic Models was created in 1985.
G. Adomian has written: 'Stochastic systems' -- subject(s): Stochastic differential equations, Stochastic systems
Wikipedia states that stochastic means random. But there are differences depending on the context. Stochastic is used as an adjective, as in stochastic process, stochastic model, or stochastic simulation, with the meaning that phenomena as analyzed has an element of uncertainty or chance (random element). If a system is not stochastic, it is deterministic. I may consider a phenomena is a random process and analyze it using a stochastic simulation model. When we generate numbers using a probability distribution, these are called random numbers, or pseudo random numbers. They can also be called random deviates. See related links.
C. W. Gardiner has written: 'Handbook of Stochastic Methods' 'Stochastic methods' -- subject(s): Stochastic processes 'Quantum noise' -- subject(s): Stochastic processes, Quantum optics, Josephson junctions