Search results for "GLM"

Vispārinātie lineārie modeļi skaita tipa datu analīzei

2022

Bakalaura darbs ir veltīts vispārināto lineāro modeļu, kas piemēroti skaita tipa datu analīzei, teorijas apskatam. Darbā apskatīts Puasona regresijas modelis, kā arī modeļi, kas piemēroti pārāk lielas dispersijas gadījumā (kvazi-Puasona un negatīvā binomiālā sadalījuma regresijas modeļi). Skaita tipa datos var būt situācijas, kad liels datu daudzums ir 0, tāpēc šādu datu analīzei aprakstīti īpaši piemēroti modeļi, jo iepriekšminētie modeļi šādiem datiem nevar sniegt korektus novērtējumus. Atsevišķi tika aprakstīta arī empīriskās ticamības funkcijas metode vispārināto lineāro modeļu koeficientu novērtēšanai un ticamības intervālu konstruēšanai, kuru var izmantot Puasona modeļa gadījumā. Darb…

Influence diagnostics for generalized linear mixed models: a gradient-like statistic

2013

In the literature, many influence measures proposed for Generalized Linear Mixed Models (GLMMs) require the information matrix that can be difficult to calculate. In the present paper, a known influence measure is approximated to get a simpler form, for which the information matrix is no more necessary. The proposed measure is showed to have a form similar to the gradient statistic, recently introduced. Good performances have been obtained through simulation studies.

Reference growth charts for assessing growth performance of Posidonia oceanica (L.) Delile

2016

Posidonia oceanica is considered a key species due to its different roles as primary producer, substrate for many species, shoreline erosion protector and long-term carbon store (1).The importance of P. oceanicahas stimulated several studies aimed at quantifying its status. In particular growth performance of rhizomes has become among the most used descriptors for monitoring changes of P. oceanicameadows induced by human or naturalexogenous factors (2). However, ability to detect any change of growth in space or in time is often confounded by natural age-induced variations, which involves serious interpretation problems (3). A general approach adopted to overcome this problem is to build gr…

The Performance of the Gradient-Like Influence Measure in Generalized Linear Mixed Models

2015

A gradient-like statistic, recently introduced as an influence measure, has been proven to work well in large sample, thanks to its asymptotic properties. In this work, through small-scale simulation schemes, the performance of such a diagnostic measure is further investigated in terms of concordance with the main influence measures used for outlier identification. The simulation studies are performed by using generalized linear mixed models (GLMMs).

Modeling temporal and spatial colony‐site dynamics in a long‐lived seabird

2003

We studied the determinants of colony site dynamics in Audouin's gull, Larus audouinii, breeding in a small archipelago of the western Mediterranean. Data on island occupation were available for a series of 25 years, since first colonization of the archipelago in 1973. Group behavior was studied in relation to the components of dispersal: permanence or abandonment (extinction) on an island previously occupied and permanence or occupation (colonization) of another island. Generalized Linear Mixed Models (GLMMs) were used to identify the relative contribution of each explanatory variable to the probability of colony abandonment. Gulls showed a low probability (3%) of abandoning one of the isl…

GLM-based automatic picking of waveforms

2011

Scale dependence of species–area relationships is widespread but generally weak in Palaearctic grasslands

2021

Questions: Species–area relationships (SARs) are fundamental for understanding biodiversity patterns and are generally well described by a power law with a constant exponent z. However, z-values sometimes vary across spatial scales. We asked whether there is a general scale dependence of z-values at fine spatial grains and which potential drivers influence it. Location: Palaearctic biogeographic realm. Methods: We used 6,696 nested-plot series of vascular plants, bryophytes and lichens from the GrassPlot database with two or more grain sizes, ranging from 0.0001 m² to 1,024 m² and covering diverse open habitats. The plots were recorded with two widespread sampling approaches (rooted presenc…

Item Response Trees: a recommended method for analyzing categorical data in behavioral studies

2015

Behavioral data are notable for presenting challenges to their statistical analysis, often due to the difficulties in measuring behavior on a quantitative scale. Instead, a range of qualitative alternative responses is recorded. These can often be understood as the outcome of a sequence of binary decisions. For example, faced by a predator, an individual may decide to flee or stay. If it stays, it may decide to freeze or display a threat and if it displays a threat, it may choose from several alternative forms of display. Here we argue that instead of being analyzed using traditional nonparametric statistics or a series of separate analyses split by response categories, this kind of data ca…

Model interpretation from the additive elements of the PWRSS in GLMMs

2013

Generalized Linear Mixed models(GLMMs)have rapidly become a widely used tool for modelling clustered and longitudinal data with non-Normal responses. Although a large amount of work has been done in the literature on likelihood-based inference on GLMMs,little seems to have been done on the decomposition of the total variability associated to the different components of a mixed model.In this work we try to generalize the idea of likelihood additive elements Whittaker,1984), proposed in the context of GLMs,to the case of GLMMs by using the Penalized Weighted Residual Sum of Squares(PWRSS). The proposal is illustrated by means of areal application.

A gradient-based deletion diagnostic measure for generalized linear mixed models

2016

ABSTRACTA gradient-statistic-based diagnostic measure is developed in the context of the generalized linear mixed models. Its performance is assessed by some real examples and simulation studies, in terms of ability in detecting influential data structures and of concordance with the most used influence measures.