kmlandkml3d:RPackages to Cluster Longitudinal Data

Génolini, Christophe; Alacoque, Xavier; Sentenac, Mariane; Arnaud, Catherine

doi:10.18637/jss.v065.i04

Cited by 235 publications

(164 citation statements)

References 60 publications

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“…This method used a hill-climbing algorithm jointly with expectation-maximization. The optimal number of clusters was chosen according to the Calinski-Harabatz criterion (Genolini et al, 2015).…”

Section: Discussionmentioning

confidence: 99%

Genetic structured antedependence and random regression models applied to the longitudinal feed conversion ratio in growing Large White pigs1

Tran

Gilbert

David

2017

Journal of Animal Science

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The objective of the present study was to compare a random regression model, usually used in genetic analyses of longitudinal data, with the structured antedependence (SAD) model to study the longitudinal feed conversion ratio (FCR) in growing Large White pigs and to propose criteria for animal selection when used for genetic evaluation. The study was based on data from 11,790 weekly FCR measures collected on 1,186 Large White male growing pigs. Random regression (RR) using orthogonal polynomial Legendre and SAD models was used to estimate genetic parameters and predict FCR-based EBV for each of the 10 wk of the test. The results demonstrated that the best SAD model (1 order of antedependence of degree 2 and a polynomial of degree 2 for the innovation variance for the genetic and permanent environmental effects, i.e., 12 parameters) provided a better fit for the data than RR with a quadratic function for the genetic and permanent environmental effects (13 parameters), with Bayesian information criteria values of -10,060 and -9,838, respectively. Heritabilities with the SAD model were higher than those of RR over the first 7 wk of the test. Genetic correlations between weeks were higher than 0.68 for short intervals between weeks and decreased to 0.08 for the SAD model and -0.39 for RR for the longest intervals. These differences in genetic parameters showed that, contrary to the RR approach, the SAD model does not suffer from border effect problems and can handle genetic correlations that tend to 0. Summarized breeding values were proposed for each approach as linear combinations of the individual weekly EBV weighted by the coefficients of the first or second eigenvector computed from the genetic covariance matrix of the additive genetic effects. These summarized breeding values isolated EBV trajectories over time, capturing either the average general value or the slope of the trajectory. Finally, applying the SAD model over a reduced period of time suggested that similar selection choices would result from the use of the records from the first 8 wk of the test. To conclude, the SAD model performed well for the genetic evaluation of longitudinal phenotypes.

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Section: Discussionmentioning

confidence: 99%

Genetic structured antedependence and random regression models applied to the longitudinal feed conversion ratio in growing Large White pigs1

Tran

Gilbert

David

2017

Journal of Animal Science

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“…Most importantly, it was observed that frost only occurred in areas on the bottom of valleys, and in particular those with slope values less than 10 (the uppermost extent of the most extreme frosts). Visual matchups were conducted by generating surface maps of frost risk (a binary no risk or high risk), exporting these as a .kml file (kml package in R; Genolini et al, 2015) to Google Earth Pro, and comparing the CAP predictions with existing vegetation boundaries evident in the imagery (Fig. 5).…”

Section: Cold Air Pooling Model Calibrationmentioning

confidence: 99%

Site selection for subtropical thicket restoration: mapping cold-air pooling in the South African sub-escarpment lowlands

Duker¹,

Cowling²,

Vyver³

et al. 2020

PeerJ

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Restoration of subtropical thicket in South Africa using the plant Portulacaria afra (an ecosystem engineer) has been hampered, in part, by selecting sites that are frost prone—this species is intolerant of frost. Identifying parts of the landscape that are exposed to frost is often challenging. Our aim is to calibrate an existing cold-air pooling (CAP) model to predict where frost is likely to occur in the valleys along the sub-escarpment lowlands (of South Africa) where thicket is dominant. We calibrated this model using two valleys that have been monitored during frost events. To test the calibrated CAP model, model predictions of frost-occurrence for six additional valleys were assessed using a qualitative visual comparison of existing treelines in six valleys—we observe a strong visual match between the predicted frost and frost-free zones with the subtropical thicket (frost-intolerant) and Nama-Karoo shrubland (frost-tolerant) treelines. In addition, we tested the model output using previously established transplant experiments; ∼300 plots planted with P. afra (known as the Thicket-Wide Plots) were established across the landscape—without consideration of frost—to assess the potential factors influencing the survival and growth of P. afra. Here we use a filtered subset of these plots (n = 70), and find that net primary production of P. afra was significantly lower in plots that the model predicted to be within the frost zone. We suggest using this calibrated CAP model as part of the site selection process when restoring subtropical thicket in sites that lie within valleys—avoiding frost zones will greatly increase the likelihood of restoration success.

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“…Data cleaning, analyses, and figures were done in R (version 3.4.0; R Development Core Team) using several packages (Bates et al 2015;Genolini et al 2015;Hijmans 2016;Liaw and Wiener 2002;Pebesma 2018;van Buuren and Groothuis-Oudshoorn 2011;Wickham 2017;Wilke 2017). Figure 1 shows the spatial distribution of built-up trajectories.…”

Section: Analysesmentioning

confidence: 99%

Land-Use Change and Cardiometabolic Risk Factors in an Urbanizing Area of South India: A Population-Based Cohort Study

Milà

Ranzani

Sanchez

et al. 2020

Environ Health Perspect

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BACKGROUND: Land-use changes in city fringes due to urbanization can lead to a reduction of greenspace that may reduce its associated health benefits. OBJECTIVES: We evaluated the association between changes in residential surrounding built-up land use and cardiometabolic risk factors in an urbanizing peri-urban area of south India and explored the mediating roles of air pollution, physical activity, and stress in these associations. METHODS: We analyzed data on 6,039 adults from the third follow-up of the Andhra Pradesh Children and Parent Study (APCAPS) cohort (2010)(2011)(2012). We generated trajectories of change in residential surrounding built-up land use (buffer areas) from 1995-2009 (stable, slow increase, fast increase) using remote sensing data and image classification methods. We estimated associations between built-up land use trajectories and natural log-transformed blood pressure, waist circumference, triglycerides, fasting glucose, and non-high-density lipoprotein (non-HDL) cholesterol using linear mixed models. We accounted for multiple mediators and the multilevel structure of the data in mediation analyses. RESULTS: We observed positive associations between a fast increase in built-up land use within 300 m of the home and all cardiometabolic risk factors. Compared with participants with stable trajectories, those with the largest increase in built-up land use had 1.5% (95% CI: 0.1, 2.9) higher systolic blood pressure, 2.4% (95% CI: 0.6, 4.3) higher diastolic blood pressure, 2.1% (95% CI: 0.5, 3.8) higher waist circumference, and 1.6% (95% CI: −0:6, 3.8) higher fasting glucose in fully adjusted models. Associations were positive, but not statistically significant, for triglycerides, fasting glucose, and non-HDL cholesterol. Physical activity and ambient particulate matter ≤2:5 lm in aerodynamic diameter (PM 2:5 ) partially mediated the estimated associations. Associations between fast build-up and all cardiometabolic risk factors except non-HDL cholesterol were stronger in women than men. DISCUSSION: Increases in built-up land use surrounding residences were consistently associated with higher levels of cardiometabolic risk factors. Our findings support the need for better integration of health considerations in urban planning in rapidly urbanizing settings. https://doi.

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kmlandkml3d:RPackages to Cluster Longitudinal Data

Cited by 235 publications

References 60 publications

Genetic structured antedependence and random regression models applied to the longitudinal feed conversion ratio in growing Large White pigs1

Genetic structured antedependence and random regression models applied to the longitudinal feed conversion ratio in growing Large White pigs1

Site selection for subtropical thicket restoration: mapping cold-air pooling in the South African sub-escarpment lowlands

Land-Use Change and Cardiometabolic Risk Factors in an Urbanizing Area of South India: A Population-Based Cohort Study

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