Metadata-Version: 2.1
Name: CasseySmithCV
Version: 0.1.0
Summary: Produces critical values using the methods described in Cassey Smith (2014).  Code is modernized from version published with paper to take advantage of advances in computing.
Project-URL: Homepage, https://github.com/tazzben/CasseySmithCV
Project-URL: Bug Tracker, https://github.com/tazzben/CasseySmithCV/issues
Author-email: Ben Smith <bosmith@unomaha.edu>
Maintainer-email: Ben Smith <bosmith@unomaha.edu>
License-Expression: MIT
License-File: LICENSE
Keywords: EG Statistic,Monte Carlo,Statistics
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Python: >=3.8
Requires-Dist: numpy>=1.21.0
Requires-Dist: pandas>=1.3.0
Requires-Dist: tqdm>=4.26.0
Description-Content-Type: text/markdown

# CasseySmithCV
 
Simulation software to generate critical values for the Ellison-Glaeser index (1997).  This is updated software from Cassey and Smith (2014); it modernizes the codebase and increases the performance of the simulations.

## Examples

Run a simulation of industries with 20 plants and sigma value of 1. 

```python
from CasseySmithCV import runSimulation, SimulationTable, SaveSimulationTable
resultDictionary = runSimulation(20,1)
```

Run all combinations of [20, 30] plants and [0.5, 1] sigma values:

```python
from CasseySmithCV import runSimulation, SimulationTable, SaveSimulationTable
resultDataFrame = SimulationTable([20, 30],[0.5, 1])
```

Run all combinations of [20, 30] plants and [0.5, 1] sigma values and save the results to a file:

```python
from CasseySmithCV import runSimulation, SimulationTable, SaveSimulationTable
SaveSimulationTable('filename.csv', [20, 30],[0.5, 1])
```

## Installation 

This package can be installed by using either the pip or conda command:

### Installing by pip

```
pip install CasseySmithCV
```

### Installing by conda

```
conda install -c tazzben casseysmithcv
```