The main objective of this research work was to develop a statistical treatment to post-process Numerical Weather Predictions (NWP) outputs in order to improve short-term wind power forecasts. The proposed method is a Model Output Statistics (MOS) based on a multiple linear regression that ...
This research addresses multiple outliers in the linear regression model. Although reliable for a single or a few outliers, standard diagnostic techniques from an ordinary least squares (OLS) fit can fail to identify multiple outliers. The parameter estimates, diagnostic quantities and model inferences...
Research and Methods Andrew C.Leon, inComprehensive Clinical Psychology, 1998 3.12.4.4.5Multiple linear regression analysis Asimplelinearregression analysisinvolves the regression of adependent variableon one independent variable.Multiplelinear regression analysis extends the statistical model such that one depe...
Multivariable linear regression is mainly used to study the relationship between a factor variable and multiple variables, similar to the principle of univariate linear regression. The difference is that there are more influence factors (arguments). In statistics, linear regression equations are the prod...
This paper presents a new technique for one-year long-term electric power load forecasting problem. The technique is suitable to forecast daily load profiles with a lead-time from several weeks to a few years. The proposed algorithm is mainly based on multiple simple linear regression models used...
Crop yield and its prediction are crucial in agricultural production planning. This study investigates and predicts arabica coffee yield in order to match the market demand, using artificial neural networks (ANN) and multiple linear regression (MLR). Dat
Many researches have been carried out in fuzzy linear regression since the past three decades. In this paper, a fuzzy linear regression model based on goal... Hassanpour,H.,Maleki,... - Asia-Pacific Journal of Operational Research 被引量: 17发表: 2009年 Fuzzy Statistical Analysis of Multipl...
Multiple linear correlation, which is the simplest and most common form of multiple correlation, is usually measured by a coefficient that ranges between zero and one (symbolized as R); it represents the highest possible degree of association between a weighted linear combination of several given pr...
This paper considers the recovery of multiple sparse vectors, with partially shared supports, from a small number of noisy linear measurements of each. It ... A Jalali,S Sanghavi - IEEE 被引量: 0发表: 2015年 Greedy dirty models: A new algorithm for multiple sparse regression for all levels...
Linear regression analysis was performed on the log-transformed (a) female recombination rate, (b) male recombination rate and (c) on the sex difference between the log-transformed rates (female–male). Full size image Previous reports have shown that recombination tend to be suppressed within ...