Inference with Linear Equality and Inequality Constraints Using R: The Package ic.infer
نویسنده
چکیده
In linear models and multivariate normal situations, prior information in linear inequality form may be encountered, or linear inequality hypotheses may be subjected to statistical tests. R package ic.infer has been developed to support inequality-constrained estimation and testing for such situations. This article gives an overview of the principles underlying inequality-constrained inference that are far less well-known than methods for unconstrained or equality-constrained models, and describes their implementation in the package.
منابع مشابه
A revisit of a mathematical model for solving fully fuzzy linear programming problem with trapezoidal fuzzy numbers
In this paper fully fuzzy linear programming (FFLP) problem with both equality and inequality constraints is considered where all the parameters and decision variables are represented by non-negative trapezoidal fuzzy numbers. According to the current approach, the FFLP problem with equality constraints first is converted into a multi–objective linear programming (MOLP) problem with crisp const...
متن کاملVOLUME MINIMIZATION WITH DISPLACEMENT CONSTRAINTS IN TOPOLOGY OPTIMIZATION OF CONTINUUM STRUCTURES
In this paper, a displacement-constrained volume-minimizing topology optimization model is present for two-dimensional continuum problems. The new model is a generalization of the displacement-constrained volume-minimizing model developed by Yi and Sui [1] in which the displacement is constrained in the loading point. In the original model the displacement constraint was formulated as an equali...
متن کاملA NEW APPROACH FOR SOLVING FULLY FUZZY QUADRATIC PROGRAMMING PROBLEMS
Quadratic programming (QP) is an optimization problem wherein one minimizes (or maximizes) a quadratic function of a finite number of decision variable subject to a finite number of linear inequality and/ or equality constraints. In this paper, a quadratic programming problem (FFQP) is considered in which all cost coefficients, constraints coefficients, and right hand side are characterized by ...
متن کاملAn inference-proof approach to privacy-preserving horizontally partitioned linear programs
Mangasarian (Optim. Lett., 6(3), 431–436, 2012) proposed a constraints transformation based approach to securely solving the horizontally partitioned linear programs among multiple entities—every entity holds its own private equality constraints. More recently, Li et al. (Optim. Lett., doi:10.1007/s11590-011-0403-2, 2012) extended the transformation approach to horizontally partitioned linear p...
متن کاملProjection Inequalities and Their Linear Preservers
This paper introduces an inequality on vectors in $mathbb{R}^n$ which compares vectors in $mathbb{R}^n$ based on the $p$-norm of their projections on $mathbb{R}^k$ ($kleq n$). For $p>0$, we say $x$ is $d$-projectionally less than or equal to $y$ with respect to $p$-norm if $sum_{i=1}^kvert x_ivert^p$ is less than or equal to $ sum_{i=1}^kvert y_ivert^p$, for every $dleq kleq n$. For...
متن کامل