Results 31 to 40 of about 1,906,785 (292)
PM2.5 concentration prediction model based on random forest regression analysis
Dianxin kexue, 2017 The random foreat regression algorithm was introduced to solve the shortcomings of neural network in predicting the PM2.5 concentration,such as over-fitting,complex network structure,low learning efficiency.A novel PM2.5 concentration prediction model ...
Xu DU, Jingyu FENG, Shaoqing LV, Wei SHI
doaj +2 more sources
Admissibility of the usual confidence interval in linear regression
, 2010 Consider a linear regression model with independent and identically normally distributed random errors. Suppose that the parameter of interest is a specified linear combination of the regression parameters. We prove that the usual confidence interval for
Giri, Khageswor +2 more
core +1 more source
Italian Journal of Animal Science, 2021 This study aimed to estimate genetic parameters of reproductive efficiency over a wide age range of females using a random regression model (RRM) in Spanish goat breeds.
Chiraz Ziadi +5 more
doaj +1 more source
Functional Lagged Regression with Sparse Noisy Observations
, 2020 A functional (lagged) time series regression model involves the regression of scalar response time series on a time series of regressors that consists of a sequence of random functions.
Panaretos, Victor M., Rubín, Tomáš
core +1 more source
Modelling heterogeneity among fitness functions using random regression [PDF]
Methods in Ecology and Evolution, 2015 Summary Statistical approaches for testing hypotheses of heterogeneity in fitness functions are needed to accommodate studies of phenotypic selection with repeated sampling across study units, populations or years. In this study, we tested directly for among‐population variation in complex fitness functions and demonstrate a new approach for locating
Richard J, Reynolds +3 more
openaire +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Objectives To identify predictors of chronic ITP (cITP) and to develop a model based on several machine learning (ML) methods to estimate the individual risk of chronicity at the timepoint of diagnosis. Methods We analyzed a longitudinal cohort of 944 children enrolled in the Intercontinental Cooperative immune thrombocytopenia (ITP) Study ...
Severin Kasser +6 more
wiley +1 more source
Jurnal Biometrika dan Kependudukan, 2018 Severe Malnutrition among under five still become a problem in East Java. Regression analysis that has been done only use data in one year so it can not see the effect of time.
Irma Ike Wahyuni, Mahmudah Mahmudah
doaj +1 more source
Journal of Dairy Science, 2022 : Ketosis is one of the most prevalent and complex metabolic disorders in high-producing dairy cows and usually detected through analyses of β-hydroxybutyrate (BHB) concentration in blood. Our main objectives were to evaluate genetic parameters for blood
W. Lou +10 more
doaj +1 more source
Random model trees: an effective and scalable regression method [PDF]
, 2010 We present and investigate ensembles of randomized model trees as a novel regression method. Such ensembles combine the scalability of tree-based methods with predictive performance rivaling the state of the art in numeric prediction.
Pfahringer, Bernhard
core +1 more source
A Simple Class of Bayesian Nonparametric Autoregression Models [PDF]
, 2013 We introduce a model for a time series of continuous outcomes, that can be expressed as fully nonparametric regression or density regression on lagged terms.
Di Lucca, Maria Anna +3 more
core +1 more source