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79 articles for “dependent variable”
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Research ArticleOpen accessIn the abstractPrediction of Body Weight of Yearling Boer Goats from Morphometric Traits using Classification and Regression TreeMadumetja Cyril Mathapo, Thobela Louis TyasiClassification and Regression Tree (CART) is a predictive algorithm method used to explains how the dependent variable can be predicted using independent variables (numerical and characters). The study was conducted to investigate the relationship between body weight and morphometric traits (Body Length (BL), Heart Girth (HG), Rump Height (RH), Rump Width (RW), Ear Length (EL), Cannon Circumference (CC) and Head … …American Journal of Animal and Veterinary Sciences, Vol. 16, Issue 2 · 3 May 2021 · 8,444 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Support and Resistance Indicators for Stock Market with Fibonacci Sequence in Long Short-Term MemoryThambusamy Velmurugan, Thiruvalluvan IndhumathyPredictive data analytics is a branch of data analytics where models are designed that effectively interpret; anticipate outcomes by analyzing present data to make predictions about future. One of the major attributes for prediction is time and there have been a considerable number of time series analytical models that are used for forecasting. Long Short-Term Memory (LSTM) is a deep … …Journal of Computer Science, Vol. 16, Issue 10 · 28 Oct 2020 · 7,323 accessesView PDFCite
Research ArticleOpen accessIn the abstractPublic Opinion About Ramadan and Obesity in EgyptDina Aly Ezzat, Augustine J. KposowaThe aim of the study was to investigate the effect of people’s perception of Ramadan eating habits and obesity in Egypt. Data were obtained through a paper and pencil cross-sectional survey that was administered to adults aged 18 and above in the Assiut Governorate in Egypt in 2015. The dependent variable was obesity, measured using the body mass index. Multivariate … …Journal of Social Sciences, Vol. 16, Issue 1 · 26 Apr 2020 · 7,372 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparison of Probit and Logistic Regression Models in the Analysis of Dichotomous OutcomesAmrutha Jose, Mariyamma Philip, Lavanya Tumkur Prasanna, M. ManjulaProbit and logistic regression models are members of the family of generalized linear models, used for estimating the functional relationship between the dichotomous dependent and independent variables. The current study is designed to find the performance of logistic and probit regression models in different conditions under multivariate normality. The objective of the study is to compare the performance of probit … …Current Research in Biostatistics, Vol. 10, Issue 1 · 26 Mar 2020 · 17,046 accessesView PDFCite
Research ArticleOpen accessIn the abstractGenetic Algorithm for Variable and Samples Selection in Multivariate Calibration ProblemsKelton de Souza Santiago, Anderson Silva Soares, Telma Woerle de Lima et al.One of the main problems of quantitative analytical chemistry is to estimate the concentration of one or more species from the values of certain physicochemical properties of the system of interest. For this it is necessary to construct a calibration model, i.e., to determine the relationship between measured properties and concentrations. The multivariate calibration is one of the most successful … …Journal of Computer Science, Vol. 11, Issue 4 · 8 Jun 2015 · 7,385 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Impact of Working Capital Turnover on Jordanian Chemical Industries’ ProfitabilityLina WarradThe chemical industry is of long-term importance to the maintain development of local economies and consider the largest industrial sectors in Jordan in terms of the exports volume which accomplished JD 1049000S in 2012. Working capital considers being a measure of company’s efficiency and its short-term financial health; moreover, it is a critical component for a business survival and a … …American Journal of Economics and Business Administration, Vol. 5, Issue 3 · 25 Feb 2014 · 7,628 accessesView PDFCite
Research ArticleOpen accessIn the abstractA TIME-DELAY CASCADING NEURAL NETWORK ARCHITECTURE FOR MODELING TIME-DEPENDENT PREDICTOR IN ONSET PREDICTIONAgus Buono, Imas Sukaesih Sitanggang, Mushthofa, Aziz KustiyoThe occurrence of rain before the real start of a rainy season often mislead farmers into thinking that rainy season has started and suggesting them to start planting immediately. In reality, rainy season has not started yet, causing the already-planted rice seed to experience dehydration. Therefore, a model that can predict the onset of rainy season is required, so that … …Journal of Computer Science, Vol. 10, Issue 6 · 29 Jan 2014 · 6,652 accessesView PDFCite
Research ArticleOpen accessIn the abstractMAXIMUM LIKELIHOOD ESTIMATION FOR SPATIAL DURBIN MODELRokhana Dwi Bekti, Anita Rahayu, SutiknoSpatial Durbin Model (SDM) is one method of spatial autoregressive. This model was developed because the dependencies in the spatial relationships not only occur in the dependent variable, but also on the independent variables. In the assessment of parameter estimation, the process is carried out by Maximum Likelihood Estimation (MLE). This estimation can be approximation by Spatial Autoregressive Models (SAR). … …Journal of Mathematics and Statistics, Vol. 9, Issue 3 · 15 Jun 2013 · 8,644 accessesView PDFCite
Research ArticleOpen accessIn the abstractObservation Modeling for Continuous Predicting Global and Diffuse Solar Radiation on Horizontal SurfaceSomporn Hongkong, Singthong PattanasethanonMathematical modeling for continuous prediction of solar energy is inevitable for energy systems. General, existing models are mostly empirical and data dependent. This article has to present a variable model for predicting global and diffuse solar radiation on the horizontal plane. The model considered in this study has applied Hidden Markov Model (HMM) with two observations. The databases were measured … …American Journal of Environmental Sciences, Vol. 9, Issue 3 · 23 May 2013 · 6,799 accessesView PDFCite
Research ArticleOpen accessIn the abstractSpatial Durbin Model to Identify Influential Factors of DiarrheaRokhana Dwi Bekti, SutiknoProblem statement: An analysis of regression modeling which influenced by the characteristics of the region is very important. That modeling is the spatial autoregressive model. One type of spatial autoregressive model is a Spatial Durbin Model (SDM), which performs a lag effect of the dependent and independent variables. This model was developed because the dependencies in the spatial relationships doesn’t … …Journal of Mathematics and Statistics, Vol. 8, Issue 3 · 13 Oct 2012 · 8,289 accessesView PDFCite