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baratadiego
GitHub 제작자 프로필

baratadiego

1개 GitHub 저장소에서 수집된 17개 skills를 저장소 단위로 보여줍니다.

수집된 skills
17
저장소
1
업데이트
2026-04-21
저장소 탐색

저장소와 대표 skills

community-ecology-ordination
동물학자·야생동물 생물학자

Performs multivariate community ecology analyses including ordination, diversity metrics, and assemblage comparisons. Use this skill when the user mentions species composition, NMDS, PCA ordination, PERMANOVA, beta diversity, alpha diversity, species richness, Bray-Curtis dissimilarity, indicator species analysis, cluster analysis, species-by-site matrices, diversity indices, or assemblage structure comparisons.

2026-04-21
predictive-modeling-best-practices
환경 과학자·전문가(보건 포함)기타 생물 과학자

Guides predictor selection, collinearity checks, cross-validation strategy, and hyperparameter tuning for ecological predictive models. Use this skill when the user mentions VIF, collinearity, feature selection, spatial cross-validation, block CV, hyperparameter tuning, overfitting prevention, data leakage auditing, background point selection, pseudo-absence generation, ENMeval tuning, regularization, or spatial autocorrelation correction.

2026-04-20
ecological-impact-assessment
환경 과학자·전문가(보건 포함)

Quantifies ecological impacts using BACI designs, landscape fragmentation metrics, and pressure indices. Use this skill when the user mentions BACI analysis, before-after-control-impact, impact assessment, disturbance effects, land use change impacts, fragmentation metrics, landscape metrics, pressure or threat indices, intervention effectiveness, management outcome evaluation, or control-impact comparisons.

2026-04-04
ecosystem-services-assessment
자연 보전 과학자환경 과학자·전문가(보건 포함)

Maps and quantifies ecosystem services including carbon stocks, water yield, soil erosion, and habitat quality with trade-off analysis. Use this skill when the user mentions ecosystem services, InVEST models, ES mapping, carbon sequestration, water yield estimation, RUSLE erosion modeling, habitat quality, pollination services, trade-off analysis, PES (payments for ecosystem services), natural capital, or ES valuation.

2026-04-04
model-validation-and-uncertainty
데이터 과학자

Validates predictive models and quantifies uncertainty including AUC/TSS metrics, calibration, extrapolation risk (MOP/MESS/ExDet), and ensemble uncertainty maps. Use this skill when the user needs model performance evaluation, ROC curves, cross-validation results, calibration curves, overfitting diagnostics, prediction intervals, bootstrap uncertainty, sensitivity/specificity assessment, or extrapolation risk analysis.

2026-04-04
biostatistics-workbench
데이터 과학자

Runs frequentist statistical analyses including GLMs, GLMMs, model selection, and assumption diagnostics for ecological data. Use this skill when the user needs statistical tests, linear or mixed models, ANOVA, effect sizes, confidence intervals, AIC-based model selection, residual diagnostics, overdispersion checks, regression analysis, p-value interpretation, normality tests, or hypothesis testing on ecological datasets.

2026-04-04
environmental-time-series
데이터 과학자

Detects trends, breakpoints, and recovery trajectories in environmental time series data from remote sensing or field measurements. Use this skill when the user mentions time series analysis, NDVI/EVI/LST trends, Mann-Kendall tests, Sen slope, BFAST breakpoints, structural change detection, seasonal decomposition (STL), anomaly detection, recovery trajectories, regime shifts, or pixel-wise trend analysis.

2026-04-04
occupancy-and-detection
데이터 과학자

Fits single-season and dynamic occupancy models that account for imperfect detection in wildlife survey data. Use this skill when the user mentions occupancy estimation, detection probability, imperfect detection, detection histories, repeated visits, MacKenzie models, psi estimation, dynamic occupancy (colonization/extinction), goodness-of-fit testing (c-hat), site occupancy, or unmarked package analyses.

2026-04-04
이 저장소에서 수집된 skills 17개 중 상위 8개를 표시합니다.
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