Statistical inferences for linear models with functional responses

2011 ◽  
Vol 21 (3) ◽  
pp. 1431-1451 ◽  
Author(s):  
Jin-Ting Zhang
Keyword(s):  
Linear Models ◽  
Functional Responses ◽  
Statistical Inferences

Numerical and functional responses of intestinal helminths in three rajid skates: evidence for competition between parasites?

Parasitology ◽  
2012 ◽  
Vol 139 (13) ◽  
pp. 1784-1793 ◽  
Author(s):  
HASEEB S. RANDHAWA
Keyword(s):  
Linear Models ◽  
Niche Breadth ◽  
Specific Interactions ◽  
Intestinal Helminths ◽  
Functional Responses ◽  
Intensity Of Infection ◽  
Host Parasite Interactions ◽  
Niche Shifts ◽  
Host Parasite ◽  
Number Of Individuals

SUMMARYHost-parasite interactions generally involve communities of parasites. Within these communities, species will co-exist and/or interact with one another in a manner either benefiting the species involved or to the detriment of one or more of the species. At the level of helminth infracommunities, evidence for intra- and inter-specific competition includes numerical responses, i.e. those regulating helminth intensity of infection, and functional responses, i.e. where the presence of competitors modifies the realised niche of infrapopulations. The objectives of this study are to assess the numerical and functional responses of helminths in infracommunities from 3 rajid skates using general linear models. Despite a lack of numerical responses, functional responses to intra- and inter-specific interactions were observed. A positive correlation between the number of individuals in an infrapopulation and its niche breadth (functional response) was observed for the tapewormsPseudanthobothriumspp. andEcheneibothriumspp., in all their respective hosts, and for the nematodePseudanisakissp. in the little skate. Evidence for inter-specific competition includes niche shifts inPseudanthobothrium purtoni(exlittle skate) andPseudanisakissp. (exthorny skate) in the presence ofPseudanisakissp. and the tapewormGrillotiasp., respectively. These results are consistent with other studies in providing evidence for competition between helminths of skates.

Linear Models for Functional Responses

2009 ◽  
pp. 147-177 ◽  
Author(s):  
J.O Ramsay ◽  
Giles Hooker ◽  
Spencer Graves
Keyword(s):  
Linear Models ◽  
Functional Responses

scholarly journals Estimation of Causal Functional Linear Regression Models

2017 ◽  
Vol 9 (6) ◽  
pp. 106
Author(s):  
J.C.S. De Miranda
Keyword(s):  
Linear Regression ◽  
Tensor Product ◽  
Linear Regression Model ◽  
Regression Models ◽  
Linear Models ◽  
Linear Regression Models ◽  
Functional Responses ◽  
Functional Linear Models ◽  
Triangular Region ◽  
Functional Linear Regression

We present a methodology for estimating causal functional linear models using orthonormal tensor product expansions. More precisely, we estimate the functional parameters $\alpha$ and $\beta$ that appear in the causal functional linear regression model:$$\mathcal{Y}(s)=\alpha(s)+\int_a^b\beta(s,t)\mathcal{X}(t)\mathrm{d}t+\mathcal{E}(s),$$ where  $\mbox{supp } \beta \subset \mathfrak{T},$ and $\mathfrak{T}$ is the closed triangular region whose vertexes are $(a,a) , (b,a)$ and $(b,b).$ We assume we have an independent sample $\{ (\mathcal{Y}_k,\mathcal{X}_k) : 1\le k \le N, k\in \mathbb{N}\}$ of observations where the $\mathcal{X}_k $'s are functional covariates, the $\mathcal{Y}_k$'s are time order preserving functional responses and $\mathcal{E}_k,$ $1\le k \le N,$ is i.i.d. zero mean functional noise.

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