Modelling Wages in Croatia Using a Second Order Polynomial Regression Model
نویسندگان
چکیده
منابع مشابه
Modelling using polynomial regression
This paper is concentrated on the polynomial regression model, which is useful when there is reason to believe that relationship between two variables is curvilinear. The polynomial regression model has been applied using the characterisation of the relationship between strains and drilling depth. Parameters of the model were estimated using a least square method. After fitting, the model was e...
متن کاملDesign of a Model Reference Adaptive Controller Using Modified MIT Rule for a Second Order System
Sometimes conventional feedback controllers may not perform well online because of the variation in process dynamics due to nonlinear actuators, changes in environmental conditions and variation in the character of the disturbances. To overcome the above problem, this paper deals with the designing of a controller for a second order system with Model Reference Adaptive Control (MRAC) scheme usi...
متن کاملRate distortion optimal signal compression using second order polynomial approximation
In this paper we present a time domain signal compression algorithm based on the coding of line segments which are used to approximate the signal. These segments are fit in a way that is optimal in the rate distortion sense. The approach is applicable to many types of signals, but in this paper we focus on the compression of ElectroCardioGram (ECG) signals. As opposed to traditional time-domain...
متن کاملSecond-order polynomial estimators from uncertain observations using covariance information
This paper presents recursive least mean-squared error second-order polynomial filtering and fixed-point smoothing algorithms to estimate a signal, from uncertain observations, when only the information on the moments up to fourth-order of the signal and observation noise is available. The estimators require the autocovariance and crosscovariance functions of the signal and their second-order p...
متن کاملNonparametric Regression Estimation under Kernel Polynomial Model for Unstructured Data
The nonparametric estimation(NE) of kernel polynomial regression (KPR) model is a powerful tool to visually depict the effect of covariates on response variable, when there exist unstructured and heterogeneous data. In this paper we introduce KPR model that is the mixture of nonparametric regression models with bootstrap algorithm, which is considered in a heterogeneous and unstructured framewo...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Business Administration
سال: 2015
ISSN: 1923-4015,1923-4007
DOI: 10.5430/ijba.v6n6p59