Dr. QuantMaster MCP Server

// Dr. QuantMaster Knowledge Base Collections // 42 domains organized into 8 categories export const COLLECTIONS = { // === FOUNDATIONS (통계 기초) === descriptive: { name: "descriptive_stats", description: "기술통계, 분포, 시각화", metadata: { category: "foundations", level: "basic" }, }, probability: { name: "probability_theory", description: "확률론, 확률분포, 중심극한정리", metadata: { category: "foundations", level: "basic" }, }, hypothesis: { name: "hypothesis_testing", description: "가설검정, t-test, ANOVA, chi-square", metadata: { category: "foundations", level: "basic" }, }, power: { name: "power_analysis", description: "검정력분석, 표본크기 계산, 효과크기", metadata: { category: "foundations", level: "intermediate" }, }, // === REGRESSION (회귀분석) === ols: { name: "ols_regression", description: "OLS, 가정, 진단, 해석", metadata: { category: "regression", level: "intermediate" }, }, logistic: { name: "logistic_regression", description: "로지스틱, 프로빗, 순서형/다항 로짓", metadata: { category: "regression", level: "intermediate" }, }, count: { name: "count_models", description: "포아송, 음이항, 영과잉 모형", metadata: { category: "regression", level: "intermediate" }, }, survival: { name: "survival_analysis", description: "생존분석, Cox, Kaplan-Meier", metadata: { category: "regression", level: "advanced" }, }, // === ECONOMETRICS (계량경제학) === panel: { name: "panel_data", description: "패널데이터, FE, RE, 하우스만", metadata: { category: "econometrics", level: "advanced" }, }, timeseries: { name: "time_series", description: "시계열, ARIMA, VAR, 공적분", metadata: { category: "econometrics", level: "advanced" }, }, iv: { name: "instrumental_variables", description: "도구변수, 2SLS, GMM", metadata: { category: "econometrics", level: "advanced" }, }, did: { name: "diff_in_diff", description: "이중차분, 평행추세, 사건연구", metadata: { category: "econometrics", level: "advanced" }, }, rdd: { name: "regression_discontinuity", description: "회귀불연속, Sharp/Fuzzy RD", metadata: { category: "econometrics", level: "advanced" }, }, synth: { name: "synthetic_control", description: "합성대조군, SCM, 인과추론", metadata: { category: "econometrics", level: "advanced" }, }, // === ADVANCED (고급 기법) === sem: { name: "structural_equation", description: "구조방정식, CFA, 경로분석", metadata: { category: "advanced", level: "advanced" }, }, mlm: { name: "multilevel", description: "다층모형, HLM, 랜덤효과", metadata: { category: "advanced", level: "advanced" }, }, bayesian: { name: "bayesian_stats", description: "베이지안, MCMC, 사전분포", metadata: { category: "advanced", level: "advanced" }, }, ml: { name: "machine_learning", description: "ML, 랜덤포레스트, XGBoost, 교차검증", metadata: { category: "advanced", level: "advanced" }, }, spatial: { name: "spatial_analysis", description: "공간분석, SAR, GWR, 공간가중행렬", metadata: { category: "advanced", level: "advanced" }, }, network: { name: "network_analysis", description: "네트워크분석, 중심성, ERGM", metadata: { category: "advanced", level: "advanced" }, }, // === META-ANALYSIS (메타분석) === metaBasic: { name: "meta_basic", description: "메타분석 기초, 효과크기, 이질성", metadata: { category: "meta", level: "intermediate" }, }, metaAdvanced: { name: "meta_advanced", description: "메타회귀, 출판편향, 민감도분석", metadata: { category: "meta", level: "advanced" }, }, // === REPLICATION (재현성/Open Science) === prereg: { name: "preregistration", description: "사전등록, OSF, AsPredicted", metadata: { category: "replication", level: "basic" }, }, openscience: { name: "open_science", description: "Open Science, FAIR, 데이터공유", metadata: { category: "replication", level: "basic" }, }, reproducibility: { name: "reproducibility", description: "재현성, 코드공유, 컨테이너", metadata: { category: "replication", level: "intermediate" }, }, // === CODE TEMPLATES (코드 템플릿) === rBasic: { name: "r_basic", description: "R 기초 코드, tidyverse, ggplot2", metadata: { category: "code", level: "basic" }, }, rAdvanced: { name: "r_advanced", description: "R 고급 코드, plm, lme4, brms", metadata: { category: "code", level: "advanced" }, }, stata: { name: "stata_code", description: "Stata 코드, xtreg, reghdfe, did", metadata: { category: "code", level: "intermediate" }, }, python: { name: "python_code", description: "Python 코드, statsmodels, sklearn", metadata: { category: "code", level: "intermediate" }, }, // === JOURNALS (저널 가이드) === econometrica: { name: "journal_econometrica", description: "Econometrica 스타일, 수식표기", metadata: { category: "journals", level: "advanced" }, }, aer: { name: "journal_aer", description: "AER 스타일, 인과추론 강조", metadata: { category: "journals", level: "advanced" }, }, jfe: { name: "journal_jfe", description: "JFE 스타일, 재무 데이터", metadata: { category: "journals", level: "advanced" }, }, ms: { name: "journal_ms", description: "Management Science 스타일", metadata: { category: "journals", level: "advanced" }, }, }; export const COLLECTION_NAMES = Object.values(COLLECTIONS).map((c) => c.name); //# sourceMappingURL=collections.js.map