On the public citation graph
Ordered Correlation Forest
0 signed · 23 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-0-387-84858-7openalex-extracted
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
inferredcites →https://doi.org/10.1007/s00181-011-0530-8openalex-extracted
Heterogeneity in health responses and anchoring vignettes
inferredcites →https://doi.org/10.1007/s00181-024-02646-4openalex-extracted
Random Forest estimation of the ordered choice model
inferredcites →https://doi.org/10.1016/j.csda.2015.10.005openalex-extracted
Random forest for ordinal responses: Prediction and variable selection
inferredcites →https://doi.org/10.1017/cbo9780511845062openalex-extracted
Modeling Ordered Choices: A Primer
inferredcites →https://doi.org/10.1017/cbo9781316576533openalex-extracted
Computer Age Statistical Inference
inferredcites →https://doi.org/10.1073/pnas.1510489113openalex-extracted
Recursive partitioning for heterogeneous causal effects
inferredcites →https://doi.org/10.1080/01621459.2017.1319839openalex-extracted
Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
inferredcites →https://doi.org/10.1111/j.1467-985x.2012.01066.xopenalex-extracted
The Heterogeneous Thresholds Ordered Response Model: Identification and Inference
inferredcites →https://doi.org/10.1111/j.2517-6161.1980.tb01109.xopenalex-extracted
Regression Models for Ordinal Data
inferredcites →https://doi.org/10.1111/j.2517-6161.1996.tb02080.xopenalex-extracted
Regression Shrinkage and Selection Via the Lasso
inferredcites →https://doi.org/10.1142/9789814513470_0006openalex-extracted
Econometric Methods for Ordered Responses: Some Recent Developments
inferredcites →https://doi.org/10.1175/1520-0450(1969)008<0985:assfpf>2.0.co;2openalex-extracted
A Scoring System for Probability Forecasts of Ranked Categories
inferredcites →https://doi.org/10.1175/1520-0493(1970)098<0917:trpsat>2.3.co;2openalex-extracted
THE RANKED PROBABILITY SCORE AND THE PROBABILITY SCORE: A COMPARISON1,,2
inferredcites →https://doi.org/10.1198/106186006x133933openalex-extracted
Unbiased Recursive Partitioning: A Conditional Inference Framework
inferredcites →https://doi.org/10.1257/jel.40.2.402openalex-extracted
What Can Economists Learn from Happiness Research?
inferredcites →https://doi.org/10.18637/jss.v077.i01openalex-extracted
ranger : A Fast Implementation of Random Forests for High Dimensional Data in C++ and R
inferredcites →https://doi.org/10.2139/ssrn.1908964openalex-extracted
High Dimensional Sparse Econometric Models: An Introduction
inferredcites →https://doi.org/10.48550/arxiv.1311.4555openalex-extracted
Confidence Intervals for Random Forests: The Jackknife and the Infinitesimal Jackknife
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.