CasseySmithCV

Name	CasseySmithCV JSON
Version	0.1.0 JSON
	download
home_page
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.
upload_time	2023-06-23 18:44:17
maintainer
docs_url	None
author
requires_python	>=3.8
license
keywords	eg statistic monte carlo statistics
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # 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
```
            

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