RSK World - Statsmodels Statistical Modeling - Project Files | RSK World

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    Website: https://rskworld.in
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        <header>
            <h1><i class="fas fa-microscope"></i> Statsmodels Statistical Modeling</h1>
            <p>Advanced Statistical Analysis and Econometric Modeling</p>
        </header>
        
        <div class="content">
            <div class="section">
                <h2>About This Project</h2>
                <p>This project demonstrates Statsmodels, a powerful library for statistical modeling and econometrics in Python. It covers linear and generalized linear models, time series analysis, hypothesis testing, statistical tests, and diagnostic tools. Perfect for statistical analysis and econometric modeling.</p>
            </div>
            
            <div class="section">
                <h2>Features</h2>
                <div class="features">
                    <div class="feature-card">
                        <h3>Linear & GLM Regression</h3>
                        <p>Comprehensive regression analysis with diagnostic tools and model validation.</p>
                    </div>
                    <div class="feature-card">
                        <h3>Time Series Analysis</h3>
                        <p>ARIMA, SARIMA models, decomposition, forecasting, and stationarity testing.</p>
                    </div>
                    <div class="feature-card">
                        <h3>Advanced Time Series</h3>
                        <p>Auto ARIMA selection, SARIMA models, comprehensive stationarity tests.</p>
                    </div>
                    <div class="feature-card">
                        <h3>Hypothesis Testing</h3>
                        <p>T-tests, ANOVA, chi-square, normality tests, and non-parametric tests.</p>
                    </div>
                    <div class="feature-card">
                        <h3>Statistical Diagnostics</h3>
                        <p>Comprehensive model diagnostics including multicollinearity, heteroscedasticity, and autocorrelation checks.</p>
                    </div>
                    <div class="feature-card">
                        <h3>Econometric Modeling</h3>
                        <p>VAR, VARMAX models, cointegration tests, impulse response functions, and Granger causality.</p>
                    </div>
                    <div class="feature-card">
                        <h3>Model Selection</h3>
                        <p>Stepwise selection, model comparison, information criteria (AIC, BIC, HQIC).</p>
                    </div>
                    <div class="feature-card">
                        <h3>Model Evaluation</h3>
                        <p>Cross-validation, time series CV, multiple metrics (MSE, MAE, R², MAPE), learning curves.</p>
                    </div>
                    <div class="feature-card">
                        <h3>Feature Selection</h3>
                        <p>VIF-based removal, correlation filtering, automated feature selection.</p>
                    </div>
                    <div class="feature-card">
                        <h3>Data Preprocessing</h3>
                        <p>Missing value handling, outlier detection/removal, scaling, stationarity transformation.</p>
                    </div>
                    <div class="feature-card">
                        <h3>Visualization</h3>
                        <p>Comprehensive plotting functions for all analyses including residuals, forecasts, and comparisons.</p>
                    </div>
                </div>
            </div>
            
            <div class="section">
                <h2>Technologies</h2>
                <div class="tech-stack">
                    <span class="tech-badge">Python</span>
                    <span class="tech-badge">Statsmodels</span>
                    <span class="tech-badge">Pandas</span>
                    <span class="tech-badge">NumPy</span>
                    <span class="tech-badge">Matplotlib</span>
                    <span class="tech-badge">Seaborn</span>
                    <span class="tech-badge">Scikit-learn</span>
                    <span class="tech-badge">SciPy</span>
                    <span class="tech-badge">Jupyter Notebook</span>
                </div>
            </div>
            
            <div class="section">
                <h2>Quick Start</h2>
                <div class="code-block">
                    <code>
# Install dependencies<br>
pip install -r requirements.txt<br><br>
# Run regression example<br>
python examples/regression_example.py<br><br>
# Run time series example<br>
python examples/time_series_example.py<br><br>
# Run hypothesis testing example<br>
python examples/hypothesis_testing_example.py
                    </code>
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            <div class="section">
                <h2>Project Structure</h2>
                <div class="code-block">
                    <code>
statsmodels-statistical/<br>
├── regression_analysis.py<br>
├── time_series_analysis.py<br>
├── advanced_time_series.py<br>
├── hypothesis_testing.py<br>
├── statistical_diagnostics.py<br>
├── econometric_modeling.py<br>
├── model_selection.py<br>
├── model_evaluation.py<br>
├── data_preprocessing.py<br>
├── visualization_utils.py<br>
├── notebooks/<br>
│   ├── 01_linear_regression.ipynb<br>
│   ├── 02_time_series.ipynb<br>
│   ├── 03_hypothesis_testing.ipynb<br>
│   └── 04_econometric_modeling.ipynb<br>
├── examples/<br>
│   ├── regression_example.py<br>
│   ├── time_series_example.py<br>
│   ├── hypothesis_testing_example.py<br>
│   ├── model_selection_example.py<br>
│   └── advanced_time_series_example.py<br>
└── data/<br>
    └── sample_data.csv
                    </code>
                </div>
            </div>
            
            <div class="author-info">
                <h3>Project Author</h3>
                <p><strong>RSK World</strong></p>
                <p>Website: <a href="https://rskworld.in" target="_blank">https://rskworld.in</a></p>
                <p>Email: <a href="mailto:help@rskworld.in">help@rskworld.in</a></p>
                <p>Phone: +91 93305 39277</p>
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            <p>&copy; 2025 RSK World. All rights reserved.</p>
            <p>Visit <a href="https://rskworld.in" target="_blank">rskworld.in</a> for more programming resources and source code.</p>
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