local regression models
TasselNetv2: in-field counting of wheat spikes with context-augmented local regression networks
... CNN-based local regression models, such as TasselNet, suffer from the problem of lacking con- textual information, so they usually cannot predict cor- rect counts when objects partially present in ...
14
Hyper-local geographically weighted regression: extending GWR through local model selection and local bandwidth optimization
... GWR models applied and demon- strated in this ...GWR models under such different parameterization ...both local bandwidths and local regression ...different local model ...
20
Hyper-local geographically weighted regression: extending GWR through local model selection and local bandwidth optimization
... GWR models under such different parameterization ...linear regression, hyper-local GWR is assessed against standard GWR, where the null hypothesis is no significant difference between ...both ...
22
GPU Friendly Local Regression for Voice Conversion
... While various models have been proposed (Stylianou et al., 1998; Toda et al., 2007; Toda et al., 2005), the most accurate ones are non-parametric because the mapping between two voices’ spectra can be highly ...
5
Local Curvature and Centering Effects in Nonlinear Regression Models
... linear models is often applied as a component of standardizing the variables in a regression, re-centering the means of the variables at ...in models when interaction terms are present in the ...
9
Local Binary Pattern and Local Linear Regression for Pose Invariant Face Recognition
... In this paper, we propose a new face recognition method that consists of two parts. One part consists of Local Linear Regression for pose invariant face images. In Recognition part, there are two methods, ...
6
Coupled Kernel Ensemble Regression
... continuous. Regression techniques used for predicting data assimilation models have received a lot of active research hot spot in recent times, particularly in real-world applica- tions ...Presently, ...
8
Semiparametric Regression Models for Interacting Covariates.
... out local polynomial estimation, and 3) add the trend back to obtain the final estimators of the ...squares regression (Glad, 1998; Martins-Filho et ...quasi-likelihood models (Fan et al., 2009) and ...
84
Flexible Regression Models for Functional Responses.
... function-on-function regression models for functional response and functional covariate observed on possible different ...These models are a generalization of the standard FLMs, and allow the ...
131
Generalized Inference in Linear Regression Models
... Since the data were collected from 5 different regions of Sarnia, we further examined whether the relationship holds in each region. Table 5.3 gives the correlation between years of living and mean number of respiratory ...
106
A Nonparametric Derivative Based Method for R Wave Detection in ECG
... utilize local polynomial nonparametric statis- tical regression to estimate the original signal and its derivative values, and then select appropriate thresholds by the ...using local polynomial ...
14
Testing for parameter instability in predictive regression models
... on models of abrupt deterministic coefficient change might be considered unattractive in practice relative to tests designed for the case where the parameters of the PR are random and evolve smoothly over ...
18
A Universal Selection Method in Linear Regression Models
... For models with a large number of regressors, the problem of establishing an effective selection algorithm is not dis- cussed in this paper; we refer to the paper ...
10
Subsampling Method for Robust Estimation of Regression Models
... ficult to formulate. With the subsampling methods, we avoid the need to formulate the outlyingness of indivi- dual observations but instead focus on the consequence of outliers, that is, they typically lead to a poor ...
16
Mapping snow depth return levels: smooth spatial modeling versus station interpolation
... ate, models 61 to 120), using the mean or location as covari- ate for σ is preferable: models 61 to 73 (blue points) have clearly higher values of TIC than models 74 to 120 (green and red points), ...
18
The effect of parental socioeconomic status on participation of pupils in special units in public primary schools in Kakamega county
... The variance in the findings could be attributed to a number of reasons. One of them could be the way special education is provided in Kenya. There are fewer private special units compared to public ones in Kakamega ...
7
Intellectual capital and its determinants in Italian listed companies
... some models attempt to investigate the contribution of individual intangible assets to a company’s market ...valuation models measures the capitalization of costs relating to training and education, as well ...
25
Beta Stacy survival regression models
... effects of birth weight found by Hutton and Pharoah [2002] this predictor was categorized in three classes, based on its 33rd and 66th percentiles, which are: [580, 2264), [2264, 3147) and [3147, 5260) grams. The prior ...
29
Calibrating a geographically weighted regression model with parameter-specific distance metrics
... where \ L is the dependent variable at location i, x ik is the value of the kth explanatory variable at location i, E i 0 is the intercept parameter at location i, E ik is the local regression parameter (or ...
6
Dynamic Integration of Regression Models
... their regression vari- ...their regression counterparts as Dynamic Selection, Dynamic Weighting and Dynamic Weighting with ...for regression remains the ...base models pre- dictions weighted ...
10