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FAME Desktop Add-in for Excel: FAME Desktop is an Excel add-in that supports the =FMD(expression, sd, ed,0, freq, orientation) and =FMS(expression, freq + date) formulas, just as the 4GL command prompt does. These formulas can be placed in Excel spreadsheets and are linked to FAME objects and analytics stored on a FAME server. Sample Excel ...
IRLS is used to find the maximum likelihood estimates of a generalized linear model, and in robust regression to find an M-estimator, as a way of mitigating the influence of outliers in an otherwise normally-distributed data set, for example, by minimizing the least absolute errors rather than the least square errors.
A common data warehouse example involves sales as the measure, with customer and product as dimensions. In each sale a customer buys a product. The data can be sliced by removing all customers except for a group under study, and then diced by grouping by product. A dimensional data element is similar to a categorical variable in statistics.
A spreadmart (spreadsheet data mart) is a business data analysis system running on spreadsheets or other desktop databases that is created and maintained by individuals or groups to perform tasks that can be done in a more structured way by a data mart or data warehouse. [1]
The basis of the method is to have, or to find, a set of simultaneous equations involving both the sample data and the unknown model parameters which are to be solved in order to define the estimates of the parameters. [1] Various components of the equations are defined in terms of the set of observed data on which the estimates are to be based.
In parametric adjustment, one can find an observation equation h(X) = Y relating observations Y explicitly in terms of parameters X (leading to the A-model below). In conditional adjustment , there exists a condition equation which is g ( Y ) = 0 involving only observations Y (leading to the B-model below) — with no parameters X at all.
In statistics, the variance inflation factor (VIF) is the ratio of the variance of a parameter estimate when fitting a full model that includes other parameters to the variance of the parameter estimate if the model is fit with only the parameter on its own. [1]
In statistics, the method of moments is a method of estimation of population parameters.The same principle is used to derive higher moments like skewness and kurtosis. It starts by expressing the population moments (i.e., the expected values of powers of the random variable under consideration) as functions of the parameters of interest.