Add to ORKGThesis sumarizes basic theory required for inference of aproximation using the least squares method and aplicates this method on data obtained from engineering practice. Within thesis were created programs, in MATLAB enviroment, to solve this problem. MATLAB already contains several algorithms, wich are useful for solving this problem. Thesis includes comparsion of properties and test of those algorithms
In this section some aspects of linear statistical models or regression models will be reviewed. Top...
This thesis is concerned with the design and implementation of a surface fitting package in an inter...
AbstractA new approach of estimating parameters in multivariate models is introduced. A fitting func...
The preferred method of data analysis of quantitative experiments is the method of least squares. Of...
Method for solving curve-fitting problems involving up to three parameters using least-squares fitti...
The contribution deals with a problem of experimental data processing by a least squares approach. A...
A method is developed for fitting a hyperplane to a set of data by least-squares, allowing for indep...
The least square method is analyzed. The basic aspects of the method are discussed. Emphasis is give...
Abstract. The course presents an overview of the least-squares technique and its variants. A wide ra...
This paper provides a minimally mathematical introduction to least-squares fitting, intended to be o...
This paper looks at solving the least squares problem and then using that theory to solve a simple m...
The Method of Least Squares is a procedure to determine the best fit line to data; the proof uses si...
A least-squares method for calculating coefficients from a linear differential equation directly fro...
A general approach for fitting a model to a data matrix by weighted least squares (WLS) is studied. ...
A formula for the least-squares best fit line was derived. A computer program was made to calculate ...
In this section some aspects of linear statistical models or regression models will be reviewed. Top...
This thesis is concerned with the design and implementation of a surface fitting package in an inter...
AbstractA new approach of estimating parameters in multivariate models is introduced. A fitting func...
The preferred method of data analysis of quantitative experiments is the method of least squares. Of...
Method for solving curve-fitting problems involving up to three parameters using least-squares fitti...
The contribution deals with a problem of experimental data processing by a least squares approach. A...
A method is developed for fitting a hyperplane to a set of data by least-squares, allowing for indep...
The least square method is analyzed. The basic aspects of the method are discussed. Emphasis is give...
Abstract. The course presents an overview of the least-squares technique and its variants. A wide ra...
This paper provides a minimally mathematical introduction to least-squares fitting, intended to be o...
This paper looks at solving the least squares problem and then using that theory to solve a simple m...
The Method of Least Squares is a procedure to determine the best fit line to data; the proof uses si...
A least-squares method for calculating coefficients from a linear differential equation directly fro...
A general approach for fitting a model to a data matrix by weighted least squares (WLS) is studied. ...
A formula for the least-squares best fit line was derived. A computer program was made to calculate ...
In this section some aspects of linear statistical models or regression models will be reviewed. Top...
This thesis is concerned with the design and implementation of a surface fitting package in an inter...
AbstractA new approach of estimating parameters in multivariate models is introduced. A fitting func...