A Package for Stochastic Nonparametric Envelopment of Data (StoNED) in Python
Project description
StoNED-Python
StoNED-Python
project provides the python codes for estimating Convex Nonparametric Least Square (CNLS
), Stochastic Nonparametric Envelopment of Data (StoNED
), and their different variants. It allows the user to estimate the CNLS/StoNED models in an open-access environment rather than in commercial software, e.g., GAMS, MATLAB. The StoNED-Python
project is built based on the PYOMO.
Authors
- Timo Kuosmanen, Professor, Aalto University School of Business.
- Sheng Dai, Ph.D. candidate, Aalto University School of Business.
To do list
-
CNLS
/StoNED
- variables returns to scale (
VRS
) model - constant returns to scale (
CRS
) model - Additive composite error term
- Multiplicative composite error term
- Residuals decomposition by method of moments(
MoM
) - Residuals decomposition by quasi-likelihood estimation(
QLE
) - Residuals decomposition by nonparametric kernel deconvolution (
NKD
)
- variables returns to scale (
-
StoNEZD
(contextual variables) - Convex quantile regression (
CQR
) - Convex expectile regression (
CER
) - Isotonic CNLS (
ICNLS
) - Isotonic convex quantile regression (
ICQR
) - Isotonic convex expectile regression (
ICER
) - Corrected convex nonparametric least squares (C2NLS)
-
StoNED
with multiple outputs - Representation of
StoNED
-related frontier/quantile function- one input and one output
- two inputs and one output
- three inputs and one output
Change log
[0.2.1] - 2020-04-23
Added
icnls()
bimatp()
Changed
- Update REDAME.md
- Update all previous functions
[0.2.0] - 2020-04-19
Added
ccnls()
ccnls2()
cnlsz()
Changed
- Update REDAME.md
- Update function
cqer()
[0.0.7] - 2020-04-18
Changed
- Update function
cnls()
[0.0.6] - 2020-04-17
Added
- README.md
- LICENSE.txt
- HISTORY.md
[0.0.2] - 2020-04-17
Added
cqer()
qllf()
[0.0.1] - 2020-04-01
Added
stoned()
cnls()
Project details
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