Implement multiple continous choices and Druedahl Jorgensen upper envelope

.pre-commit-config.yaml

@@ -59,7 +59,7 @@ repos:
 #    hooks:
 #      - id: setup-cfg-fmt
   - repo: https://github.com/psf/black-pre-commit-mirror
-    rev: 26.1.0
+    rev: 26.3.1
     hooks:
       - id: black
         language_version: python3.13
@@ -76,6 +76,7 @@ repos:
     rev: v1.7.7
     hooks:
       - id: docformatter
+        language_version: python3.13
         args:
           - --in-place
           - --wrap-summaries

docs/source/background/limitations.rst

@@ -9,7 +9,7 @@ However, there are limitations to what kind of features can be implemented and h
 
 Below we discuss what kind of models `dcegm` is designed for and importantly what limitations to be aware of when implementing a model.
 
-What can dcegm do?
+What can `dcegm` do?
 ---------------------
 
 The package follows Ishakov et al. (2017) and implements the discrete-continuous endogenous grid method (DC-EGM) for solving dynamic stochastic optimization problems with both discrete and continuous choices. Our code originated as a Python replication of their Matlab code and has since been extended to include additional features and improvements (such as used in Iskhakov and Keane (2021)).
@@ -25,7 +25,6 @@ What can `dcegm` not be used for?
 ---------------------------------
 
 - Purely discrete choice models (see e.g. Keane and Wolpin; 1997)
-- Models with more than two continuous state variables.
 - Models with more than one continuous state variable with a normally distributed idiosyncratic shock.
 
 

docs/source/background/sparsity_conditions.rst

@@ -15,6 +15,8 @@ To ensure that only **feasible** and **logically consistent** states are evaluat
 1. **Filters** out invalid state combinations that violate model logic (e.g., working while dead).
 2. **Returns** cleaned or adjusted versions of the state variables to account for absorbing states (e.g., setting `job_offer = 0` when dead).
 
+Note that sparsity conditions can only be defined for discrete state variables.
+
 Basic Structure of a Sparsity Condition
 ---------------------------------------