Search results for "simple linear regression"
showing 10 items of 11 documents
Comparative analysis of different techniques for spatial interpolation of rainfall data to create a serially complete monthly time series of precipit…
2011
Abstract The availability of good and reliable rainfall data is fundamental for most hydrological analyses and for the design and management of water resources systems. However, in practice, precipitation records often suffer from missing data values mainly due to malfunctioning of raingauge for specific time periods. This is an important issue in practical hydrology because it affects the continuity of rainfall data and ultimately influences the results of hydrologic studies which use rainfall as input. Many methods to estimate missing rainfall data have been proposed in literature and, among these, most are based on spatial interpolation algorithms. In this paper different spatial interpo…
The exchange rates – indicators for assessing the financial performance of the companies from Romania
2016
Abstract The research aims to determine the financial performance of the companies listed and traded on the Bucharest Stock Exchange from the manufacturing sector in Romania, compared with the performance recorded by the Bucharest Stock Exchange, based on the exchange rates. It was concluded that the financial performance of the companies included in the research, quantified on the basis of the exchange rates, decreased significantly with the arrival of the financial and economic crisis, currently, the companies being unable to reach the level of performance recorded before the crisis.
Differential geometric least angle regression: a differential geometric approach to sparse generalized linear models
2013
Summary Sparsity is an essential feature of many contemporary data problems. Remote sensing, various forms of automated screening and other high throughput measurement devices collect a large amount of information, typically about few independent statistical subjects or units. In certain cases it is reasonable to assume that the underlying process generating the data is itself sparse, in the sense that only a few of the measured variables are involved in the process. We propose an explicit method of monotonically decreasing sparsity for outcomes that can be modelled by an exponential family. In our approach we generalize the equiangular condition in a generalized linear model. Although the …
Empirical determination of the average annual runoff coefficient in the Mediterranean area
2014
Runoff estimation in ungauged basin is a challenge for the hydrological engineers and planners. For an y hydrological study on an ungauged basin, a methodology has to be appropriately selected for the determination of runoff at its outlet. Several meth ods have been used to estimate the basin runoff production. In this study the empirical Kennessey m ethod to determine average annual runoff coefficien t, RC, is tested on 61 Sicilian basins characterized b y different climate conditions, surface permeabilit y, mean slope and vegetation cover. A comparison between observed and calculated RC showed that a calibration of the Kennessey model could be necessary. The slight and not satisfying impr…
Alternating model trees
2015
Model tree induction is a popular method for tackling regression problems requiring interpretable models. Model trees are decision trees with multiple linear regression models at the leaf nodes. In this paper, we propose a method for growing alternating model trees, a form of option tree for regression problems. The motivation is that alternating decision trees achieve high accuracy in classification problems because they represent an ensemble classifier as a single tree structure. As in alternating decision trees for classification, our alternating model trees for regression contain splitter and prediction nodes, but we use simple linear regression functions as opposed to constant predicto…
The Norm-P Estimation of Location, Scale and Simple Linear Regression Parameters
1989
A new formulation of the exponential power distributions is used as general error model to describe long-tailed and short -tailed distributed errors. The proposed estimators of the location, scale and structure parameters of this general model and of the simple linear regression parameters when the response variable is affected by errors coming from the previous model should be used instead of robust estimators and against the practice of rejecting outlying observations. Two Monte Carlo simulations prove the good properties of these norm-p estimators.
Simulation in the Simple Linear Regression Model
2002
Summary This article presents an activity which simulates the linear regression model in order to verify the probabilistic behaviour of the resulting least-squares statistics in practice.
Linear and nonlinear interest rate sensitivity of Spanish banks
2011
Abstract Interest rate risk is one of the major financial risks faced by banks due to the very nature of the banking business. The most common approach in the literature has been to estimate the impact of interest rate risk on banks using a simple linear regression model. However, the relationship between interest rate changes and bank stock returns does not need to be exclusively linear. This article provides a comprehensive analysis of the interest rate exposure of the Spanish banking industry employing both parametric and non-parametric estimation methods. Its main contribution is to use, for the first time in the context of banks’ interest rate risk, a nonparametric regression technique…
Linear and ellipsoidal restrictions in linear regression
1991
The problem of combining linear and ellipsoidal restrictions in linear regression is investigated. Necessary and sufficient conditions for compactness of the restriction set are proved assuring the existence of a minimax estimator. When the restriction set is not compact a minimax estimator may still exist for special loss functions arid regression designs
Economic development and agriculture: Managing protected areas and safeguarding the environment
2017
Abstract The establishment of protected areas has been one of the most important interventions to protect biodiversity from the threat of human activities and in particular from the agricultural traditional activities where they have been restricted at the expense of the economy of the territory sparking in literature a heated debate between those who argue the these hinder the socio-economic development and on the other hand are those who argue that is able to advance social welfare. On the basis of these considerations, the weight of agricultural sector of a country is highly linked to the percentage of protected areas even though the trend of the weight of agriculture in the overall econ…