Erişim şekli için "info:eu-repo/semantics/closedAccess" İstatistik Bölümü Koleksiyonu listeleme
Toplam kayıt 36, listelenen: 1-20
-
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 ... -
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, ... -
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 ... -
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 ... -
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 ... -
Consistency and Asymptotic Normality of Estimator for Parameters in Multiresponse Multipredictor Semiparametric Regression Model
(MDPI, 2022)A multiresponse multipredictor semiparametric regression (MMSR) model is a combination of parametric and nonparametric regressions models with more than one predictor and response variables where there is correlation between ... -
Criteria for Best Architecture Selection in Artificial Neural Networks
(World Scientific Publishing Co., 2022)Architecture selection in artificial neural networks is a critical process which determines a satisfactory neural network model(s) that will lead to the most accurate results. The architecture that minimizes the difference ... -
Determining confidence interval and asymptotic distribution for parameters of multiresponse semiparametric regression model using smoothing spline estimator
(Elsevier B.V., 2023)The multiresponse semiparametric regression (MSR) model is a regression model with more than two response variables that are mutually correlated, and its regression function is composed of parametric and nonparametric ... -
Determining the Flat Sales Prices by Flat Characteristics Using Bayesian Network Models
(Springer, 2021)There are various factors affecting flat sales prices. Various characteristics of a flat play an important role in determining its sales price. In this study, a machine learning based Bayesian network was built by a ... -
Dynamic panel fuzzy time series model and its application to econometric time series
(Elsevier, 2021)This study proposes a new Fuzzy Time Series (FTS) approach, called as Dynamic Panel Fuzzy Time Series (DPFTS) which combines Dynamic Panel Data Analysis and FTS. The major advantages of proposed approach can be summarized ... -
Evaluating prophylactic heparin in ambulatory patients with solid tumours: a systematic review and individual participant data meta-analysis
(Elsevier Sci Ltd, 2020)Background Study-level meta-analyses provide high-certainty evidence that heparin reduces the risk of symptomatic venous thromboembolism for patients with cancer; however, whether the benefits and harms associated with ... -
Event-Oriented, Model-Based GUI Testing and Reliability Assessment-Approach and Case Study
(Elsevier Academic Press Inc, 2012)It is widely accepted that graphical user interfaces (GUIs) highly affect-positive or negative-the quality and reliability of human-machine systems. However, quantitative assessment of the reliability of GUIs is a relatively ... -
Fire behavior prediction with artificial intelligence in thinned black pine (Pinus nigra Arnold) stand
(Elsevier B.V., 2023)Modeling forest fire behavior is very important for the effective control of forest fires and the setting up of necessary precautions before fires start. However, studies of forest fire behavior are complex studies that ... -
Imputation Method Based on Sliding Window for Right-Censored Data
(Springer, 2020)Censored data arise in almost all important statistical analyses. For example, in patient-based studies, biostatistics data often subject to right censoring due to the detection limits, or to incomplete data. In the context ... -
The Khorana score for prediction of venous thromboembolism in cancer patients: An individual patient data meta-analysis
(Wiley, 2020)Background Oncology guidelines suggest using the Khorana score to select ambulatory cancer patients receiving chemotherapy for primary venous thromboembolism (VTE) prevention, but its performance in different cancers remains ... -
Large-scale global optimization based on hybrid swarm intelligence algorithm
(IOS Press, 2020)There are numerous large-scale global optimization problems encountered in real-world applications including engineering, manufacturing, economics, networking fields. Over the last two decades different varieties of swarm ... -
Mapping the forest fire risk zones using artificial intelligence with risk factors data
(SPRINGER HEIDELBERG, 2022)Geographical information system data has been used in forest fire risk zone mapping studies commonly. However, forest fires are caused by many factors, which cannot be explained only by geographical and meteorological ... -
Modeling of Tunnel Boring Machine Performance Employing Random Forest Algorithm
(Springer Science and Business Media Deutschland GmbH, 2023)Prediction of tunnel boring machine (TBM) performance is still a challenging research subject in engineering geology, geotechnical engineering, and tunnel engineering communities. The longest railway tunnel with approximately ...