fixed not visible percentage

Author: steven-ja

content/posts/finance/stock_prediction/SARIMA/index.md

@@ -305,7 +305,7 @@ plt.show()
 ![png](images/sarima_example_9_1.png)
 
 As the previous plot shows, SARIMA model takes into account stagionality with respect to the [ARIMA model]((/posts/finance/stock_prediction/arima/)) and provides better accuracy and *mape* score (5% vs. 7%). Moreover, the stagionality can deal with temporary detachment from the mean value.
-Nonetheless, SARIMA model is slower to train and to interfer (respectively $\approx 100%$ and $50%$ more). It still does not involve exogenous variables (possible with SARIMAX) and potential outbreaks (like Covid-19 or holidays).
+Nonetheless, SARIMA model is slower to train and to interfer (respectively $\approx 100\\% $ and $50\\%$ more). It still does not involve exogenous variables (possible with SARIMAX) and potential outbreaks (like Covid-19 or holidays).
 
 
 

public/index.json

@@ -759,7 +759,7 @@ <h2 id="4-sarima-model-implementation">4. SARIMA Model Implementation</h2>
 </span></span><span style="display:flex;"><span>plt<span style="color:#f92672">.</span>show()
 </span></span></code></pre></div><p><img alt="png" src="/posts/finance/stock_prediction/sarima/images/sarima_example_9_1.png"></p>
 <p>As the previous plot shows, SARIMA model takes into account stagionality with respect to the <a href="%28/posts/finance/stock_prediction/arima/%29">ARIMA model</a> and provides better accuracy and <em>mape</em> score (5% vs. 7%). Moreover, the stagionality can deal with temporary detachment from the mean value.
-Nonetheless, SARIMA model is slower to train and to interfer (respectively $\approx 100%$ and $50%$ more). It still does not involve exogenous variables (possible with SARIMAX) and potential outbreaks (like Covid-19 or holidays).</p>
+Nonetheless, SARIMA model is slower to train and to interfer (respectively $\approx 100\% $ and $50\%$ more). It still does not involve exogenous variables (possible with SARIMAX) and potential outbreaks (like Covid-19 or holidays).</p>
 <h2 id="5-model-diagnostics">5. Model Diagnostics</h2>
 <p>After fitting the model, it&rsquo;s important to check its adequacy:</p>
 <div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-python" data-lang="python"><span style="display:flex;"><span><span style="color:#75715e"># Model diagnostics</span>