The iterative proportional fitting procedure (IPF or IPFP, also known as biproportional fitting or biproportion in statistics or economics (input-output...

Raking (also called "raking ratio estimation" or "iterative proportional fitting") is the statistical process of adjusting data sample weights of a contingency...

mathematical methods to attain biproportionality. One method is called iterative proportional fitting (IPF). It was proposed for elections by the mathematician Michel...

ras, a SunOS raster format RAS algorithm, an algorithm for iterative proportional fitting in economics RAS supergroup or SAR supergroup, a plant clade...

Ontario, Canada Ipf (mountain), a mountain in southern Germany Iterative proportional fitting, estimates values in an N-dimensional matrix YPF, an Argentinian...

questionnaires, and documents. Data cleansing Data editing Iterative proportional fitting for a method of data enhancement applied in statistics, economics...

analyzed its convergence. This is essentially the same as the Iterative proportional fitting algorithm, well known in survey statistics. The following analogue...

response theory Item-total correlation Item tree analysis Iterative proportional fitting Iteratively reweighted least squares Itô calculus Itô isometry Itô's...

Tables is a tool for generating and printing crosstabs. The iterative proportional fitting procedure essentially manipulates contingency tables to match...

1940 U.S. Census, formulating the Deming-Stephan algorithm for iterative proportional fitting in the process. During World War II, Deming was a member of...

condition. Data editing Data management Data mining Database repair Iterative proportional fitting Record linkage Single customer view Triangulation (social science)...

there are zero entries in matrix Z {\displaystyle Z} . The iterative proportional fitting procedure (IPF) is also a function: IPF ( Z , Y e m T , e n...

closed-form solution. The nonlinear problem is usually solved by iterative refinement; at each iteration the system is approximated by a linear one, and thus the...

time consuming to be evaluate repeatedly, as it is often the case in iterative minimization algorithms. In the Linear Template Fit, the residuals are...

{\displaystyle K_{i},K_{j}} = balancing factors solved iteratively. See Iterative proportional fitting. f {\displaystyle f} = distance decay factor, as in...

his death. Together with W. Edwards Deming, he introduced the iterative proportional fitting algorithm to estimate cell probabilities in contingency tables...

Older models include the Fratar or Furness method, a type of iterative proportional fitting. Mode choice computes the proportion of trips between each origin...

compute the first few PCs. The non-linear iterative partial least squares (NIPALS) algorithm updates iterative approximations to the leading scores and...

data editing Data cleansing Data pre-processing Data wrangling Iterative proportional fitting Triangulation (social science) the errors that have a substantial...

linear regression of ln(y) on x, a computation that does not require iterative optimization. However, use of a nonlinear transformation requires caution...

In statistics, the ordered logit model or proportional odds logistic regression is an ordinal regression model—that is, a regression model for ordinal...

In statistics, an expectation–maximization (EM) algorithm is an iterative method to find (local) maximum likelihood or maximum a posteriori (MAP) estimates...

packages. Other approaches, including Bayesian regression and least squares fitting to variance stabilized responses, have been developed. Ordinary linear...

method for unconstrained mathematical optimization. It is a first-order iterative algorithm for minimizing a differentiable multivariate function. The idea...

weighted least squares estimator may be used to account for that. Curve fitting Line regression Local polynomial regression Polynomial and rational function...

algorithms as iterative functional gradient descent algorithms. That is, algorithms that optimize a cost function over function space by iteratively choosing...

methods by directly addressing constraints analytically and avoiding iterative procedures, although it cannot currently handle inequality constraints...

equation. While the Colebrook–White relation is, in the general case, an iterative method, the Swamee–Jain equation allows fD to be found directly for full...

closed-form expression,: 718  which takes linear time, rather than by expensive iterative approximation as used for many other types of classifiers. In the statistics...

floating point numbers, in an iterative manner. The precision of the floating-point numbers is gradually increased in each iteration, by using GNU MPFR. Once...