Data smoothing algorithms, Advanced Statistics

Assignment Help:

The procedures for extracting the pattern in a series of observations when this is obscured by the noise. Basically any such technique or method separates the original series into a smooth sequence and the residual sequence (usually called the 'rough'). For instance, a smoother can separate seasonal Fluctuations from the briefer events such as identifiable peaks and random noise. A simple example of such a process is the moving average; a more complex one is locally weighted regression.


Related Discussions:- Data smoothing algorithms

Describe monty hall problem, Monty Hall problem : A apparently counter-intu...

Monty Hall problem : A apparently counter-intuitive problem in the probability which gets its name from the TV game show, 'Let's Make a Deal' hosted by the Monty Hall. On show a pa

Decision tree, The graphic representation of the alternatives in a decision...

The graphic representation of the alternatives in a decision making problem which summarizes all the possibilities foreseen by the decision maker. For instance, suppose we are give

Inferetial statistics, wat iz z difference b/n logistic regression and mul...

wat iz z difference b/n logistic regression and multiple regression analysis /

Chance events, Chance events : According to the Cicero these are events whi...

Chance events : According to the Cicero these are events which occurred or will occur in ways which are the uncertain-events which may happen, may not happen, or may happen in some

Comparative exposure rate, Comparative exposure rate : A measure of allianc...

Comparative exposure rate : A measure of alliance for use in a matched case-control study, de?ned as the ratio of the number of case-control pairs, where the case has greater expos

Gauss markov theorem, This is the theorem which states that if the error te...

This is the theorem which states that if the error terms in a multiple regression have the same variance and are not corrected, then the estimators of the parameters in the model p

Whites general heteroscedasticity test, The Null Hypothesis - H0:  γ 1 = γ...

The Null Hypothesis - H0:  γ 1 = γ 2 = ...  =  0  i.e.  there is no heteroscedasticity in the model The Alternative Hypothesis - H1:  at least one of the γ i 's are not equal

Finite population correction, This term sometimes used to describe the extr...

This term sometimes used to describe the extra factor in variance of the sample mean when n sample values are drawn without the replacement from the finite population of size N. Th

Define kalman filter, Kalman filter : A recursive procedure which gives an ...

Kalman filter : A recursive procedure which gives an estimate of the signal when only the 'noisy signal' can be observed. The estimate is efficiently constructed by putting the exp

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd