Başlık için İstatistik Bölümü Koleksiyonu listeleme
Toplam kayıt 95, listelenen: 1-20
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Adaptive kernel density estimation with generalized least square cross-validation
(Hacettepe Univ, Fac Sci, 2019)Adaptive kernel density estimator is an efficient estimator when the density to be estimated has long tail or multi-mode. They use varying bandwidths at each observation point by adapting a fixed bandwidth for data. It is ... -
Adaptive Weighted Performance Criterion for Artificial Neural Networks
(Ieee, 2018)Extended Weighted Performance Criterion (EWPC) which is motivated from Weighted Information Criterion (WIC) has been shown promising results in previous study and results of the application showed that EWPC is capable of ... -
An adjustment degree of fitting on fuzzy linear regression model toward manufacturing income
(Institute of Advanced Engineering and Science, 2023)The regression analysis is a common tool in data analysis, while fuzzy regression can be used to analyze uncertain or imprecise data. Manufacturing companies often having difficulty predicting their future income. Thus, a ... -
Analysis of the Relations Between Forestry Financial Supports and Forest Crimes
(PMC, 2022)Forest crimes are among the serious threats destroying forests. To prevent the forest crimes there are various solutions proposed, such as fortification of the laws, increasing the penalties, or increasing the public ... -
Analyzing the Validity of Selective Mutation with Dominator Mutants
(Assoc Computing Machinery, 2016)Various forms of selective mutation testing have long been accepted as valid approximations to full mutation testing. This paper presents counterevidence to traditional selective mutation. The recent development of dominator ... -
Are most proposed ridge parameter estimators skewed and do they have any effect on MSE values?
(Taylor and Francis Ltd., 2021)Multicollinearity is a common problem in multiple regression that occurs whenever two or more explanatory variables are highly correlated. When multicollinearity exists, the method of Ordinary Least Square (OLS) is likely ... -
Assessment of the effects of the biotic and abiotic harmful factors on the amount of industrial wood production with deep learning
(Springer Science and Business Media Deutschland GmbH, 2023)The protection and sustainability of forest assets is possible with planned production of forest products to lead to minimum loss. One of the products obtained from forests is the industrial wood, which is the most important ... -
Bandwidth Selection Problem for Nonparametric Regression Model with Right-Censored Data
(Natl Inst Statistics, 2017)In this paper, the proposed estimator for the unknown nonparametric regression function is a Nadarya-Watson (Nadarya, 1964; Watson, 1964) type kernel estimator. In this estimation procedure, the censored observations are ... -
A Bayesian network model for prediction and analysis of possible forest fire causes
(Elsevier, 2019)Possible causes of a forest fire ignition could be human-caused (arson, smoking, hunting, picnic fire, shepherd fire, stubble burning) or natural-caused (lightning strikes, power lines). Temperature, relative humidity, ... -
Censored Nonparametric Time-Series Analysis with Autoregressive Error Models
(Springer, 2020)This paper focuses on nonparametric regression modeling of time-series observations with data irregularities, such as censoring due to a cutoff value. In general, researchers do not prefer to put up with censored cases in ... -
Choice of smoothing parameter for kernel type ridge estimators in semiparametric regression models
(National Statistical Institute, 2021)This paper concerns kernel-type ridge estimators of parameters in a semiparametric model. These estimators are a generalization of the well-known Speckman’s approach based on kernel smoothing method. The most important ... -
Classification of Cancer Types by Cluster Analysis Methods
(Bahadır Fatih YILDIRIM, 2021)Cluster analysis can be defined as the group of methods that aim to classify multivariate observations by using similarity/dissimilarity measures between observations. The clusters obtained as a result of the analysis are ... -
Clustering of football players based on performance data and aggregated clustering validity indexes
(WALTER DE GRUYTER GMBH, 2023)We analyse football (soccer) player performance data with mixed type variables from the 2014-15 season of eight European major leagues. We cluster these data based on a tailor-made dissimilarity measure. In order to decide ... -
Comparing clusterings and numbers of clusters by aggregation of calibrated clustering validity indexes
(Springer, 2020)A key issue in cluster analysis is the choice of an appropriate clustering method and the determination of the best number of clusters. Different clusterings are optimal on the same data set according to different criteria, ... -
A comparison between the Bayesian network model and the logistic regression model in prevention of the defects on ceramic tiles
(Taylor and Francis Ltd., 2022)One of the most important problems encountered in ceramic tile industry is defective product problem. Defective ceramics lead to loss of income and waste of resources in enterprises. However, it is generally unknown that ... -
Comparison of Different Count Models for Investigation of Some Environmental Factors Affecting Stillbirth in Holsteins
(Agricultural Research Communication Centre, 2022)Background: The objective of this study is comparing different count data models for stillbirth data. In modeling this type of data, Poisson regression or alternative models can be preferred. Methods: The poisson, negative ... -
Comparison of fuzzy logic based models for the multi-response surface problems with replicated response measures
(Elsevier, 2015)A replicated multi-response experiment is a process that includes more than one responses with replications. One of the main objectives in these experiments is to estimate the unknown relationship between responses and ... -
Comparison of parametric and semi-parametric models with randomly right-censored data by weighted estimators: Two applications in colon cancer and hepatocellular carcinoma datasets
(SAGE Publications Inc., 2021)In this study, parametric and semi-parametric regression models are examined for random right censorship. The components of the aforementioned regression models are estimated with weights based on Cox and Kaplan-Meier ... -
Comparison of partial least squares with other prediction methods via generated data
(Taylor & Francis Ltd, 2020)The purpose of this study is to compare the Partial Least Squares (PLS), Ridge Regression (RR) and Principal Components Regression (PCR) methods, used to fit regressors with severe multicollinearity against a dependent ... -
The Comparison of Performances of Widely Used Cointegration Tests
(Taylor & Francis Inc, 2016)The aim of this study is to compare performances of commonly cointegration tests used in literature in terms of their empirical power and type I error probabilty for various sample sizes. As a result of the study, it has ...
