This study developed a new model using polynomial regression based on actual data collected from a residential project in Kuala Lumpur, Malaysia. The study examined how rebar work is influenced by five weather factors: temperature, relative humidity, solar radiation, wind speed, and rainfall. The ...
For each treatment and dose time-resolved quantitative LC–MS analysis was performed and analyzed with longitudinal data analysis (Supplementary Methods) using a polynomial regression model (degree ≤ 2)33. This yielded for each protein an estimation of its temporal response as well as the sign...
Using a fractional polynomial analysis with a multivariable proportional hazards regression model, we confirmed the assumption of linearity in the log hazard ... R Leon-Ferre,J Carter,D Zahrieh,... - 《Cancer Research》 被引量: 0发表: 2023年 Multivariable Fractional Polynomials for lithium-ion ...
The influences of W/P, cement and PFA contents, and the dosage of SP were characterised and analysed using polynomial regression, which can identify the primary factors and their interactions on the measured properties. The results show tha MS-SCC can be achieved with a 28-day compressive ...
Mild nonlinearities can to some degree be modelled by polynomial regression, using e.g. square- and interaction terms as extra regressors [12], but a robust metamodelling methodology must be capable also of handling strong nonlinearities, in particular non-monotone input-output relationships [13–...
poly.regressionsmoothing data in time-series and imputing missing (NA) values using polynomial regression poly_trendDerives Nth order polynomial trend with confidence intervals pp.subsampleGenerates random subsample based on point process intensity function of the observed data. This is a spatially informe...
In multiple imputation, the incomplete variables are imputed using regression mod- els based on other covariates that are used to estimate a likely value for each of the incomplete patients. However, not the estimated value is imputed, but the estimated value to which a random error term (...
Automatic kernel regression modelling using combined leave-one-out test score and regularised orthogonal least squares This paper introduces an automatic robust nonlinear identificationalgorithm using the leave-one-out test score also known as the PRESS(Predicted REsidual S... X Hong,S Chen,PM Sharke...
On the other hand, metamodels can be used instead as an alternative approach, response surface metamodels (RSMs), particularly, polynomial regression metamodels (PRMs) being the most commonly preferred ones. However, existence of extreme observations in data may cause statistically invalid ...
Using some logarithmic and integral transformation we transform a continuous covariate frailty model into a polynomial regression model with a random effec... I López-De-Ullibarri,P Janssen,R Cao - 《Journal of Statistical Planning & Inference》 被引量: 8发表: 2012年 Jitter Suppression in a ...