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* Add Statistics Menu * Add Granger Causality test * Apply Black formatting * Add Cointegration Tests * Adjust plotting for Cointegration test * Add Significant parameter to Cointegration tests * Move regression functions to seperate .py files * Progress on Panel Data * A lot of progress for Panel Data * Make functions robust and improve documentation * Re-enable Breusch-Godfrey * Add modify functionality * Improve modify functionality * Add Breusch-Pagan heteroscedasticity test * Capitalize a word * Include documentatin for the Statistics Menu * Update _index.md * Update _index.md * Update _index.md * Fix export statements and add Example datasets * Update example with Longley's dataset * Update documentation with a legit source * Compare the results from each regression models based on the wage_panel dataset * Updated with all relevant types of regression tables * Update with all relevant regression types for Panel data * Update _index.md * Add change column type, improve OLS, add time and entity effects for FE * Update documentation and fix a small bug * Add in Statistics menu, replacing Custom menu * Remove custom menu * Add in documentation * Add in gst files * Cointegration can be used on any amount of columns * Add Tests * Make tests time invariant * Update Poetry and Requirements * Change name of Statistics menu to Econometrics menu * Rename scripts * Add type in Documentation * Change names from Statistics to Econometrics * Add graph * Update tests with rounding and naming * Make minor adjustments to fix the tests * Updating tests : allow extra args for capture * Apply recorder formatting * Adding some minor formatting * Fix error with MyPy * Attempt to fix MyPy annoyance * super small style things * Fix small bugs and add plot command to dwat * Small description mistake * Update documentation with missing argument * Update styling * Add error handling and add improve show functionality * Fix merge issue * Allow import from custom_imports Co-authored-by: Jeroen Bouma <jeroenbouma@MacBook-Pro-van-Jeroen.local> Co-authored-by: jmaslek <jmaslek11@gmail.com> Co-authored-by: Chavithra PARANA <chavithra@gmail.com>
3.3 KiB
Vendored
3.3 KiB
Vendored
usage: dwat [-p] [-h] [--export {csv,json,xlsx}]
Show autocorrelation tests from Durbin-Watson
The Durbin Watson (DW) statistic is a test for autocorrelation in the residuals from a statistical model or regression analysis. The Durbin-Watson statistic will always have a value ranging between 0 and 4. A value of 2.0 indicates there is no autocorrelation detected in the sample. Values from 0 to less than 2 point to positive autocorrelation and values from 2 to 4 means negative autocorrelation. [Source: Investopedia]
optional arguments:
-p, --plot Plot the residuals (default: False)
-h, --help show this help message (default: False)
--export {csv,json,xlsx}
Export raw data into csv, json, xlsx (default: )
Example:
2022 Feb 24, 05:59 (✨) /econometrics/ $ ols adj_close-msft adj_close-aapl adj_close-googl adj_close-tsla
OLS Regression Results
==============================================================================
Dep. Variable: adj_close_msft R-squared: 0.977
Model: OLS Adj. R-squared: 0.977
Method: Least Squares F-statistic: 1.068e+04
Date: Thu, 24 Feb 2022 Prob (F-statistic): 0.00
Time: 12:00:01 Log-Likelihood: -2830.6
No. Observations: 759 AIC: 5669.
Df Residuals: 755 BIC: 5688.
Df Model: 3
Covariance Type: nonrobust
===================================================================================
coef std err t P>|t| [0.025 0.975]
-----------------------------------------------------------------------------------
Intercept 27.7984 2.166 12.832 0.000 23.546 32.051
adj_close_aapl 0.8662 0.034 25.503 0.000 0.800 0.933
adj_close_googl 0.0508 0.002 30.374 0.000 0.048 0.054
adj_close_tsla -0.0007 0.004 -0.181 0.856 -0.009 0.007
==============================================================================
Omnibus: 41.445 Durbin-Watson: 0.044
Prob(Omnibus): 0.000 Jarque-Bera (JB): 47.398
Skew: 0.612 Prob(JB): 5.10e-11
Kurtosis: 2.995 Cond. No. 1.16e+04
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
[2] The condition number is large, 1.16e+04. This might indicate that there are
strong multicollinearity or other numerical problems.
2022 Feb 24, 06:00 (✨) /statistics/ $ dwat -p
The result 0.04 is outside the range 1.5 and 2.5 and therefore autocorrelation can be problematic.
Please consider lags of the dependent or independent variable.
