published archm=TRUE

Author: englianhu

README.html

@@ -103,71 +103,10 @@
 <div class="container-fluid main-container">
 
 <!-- tabsets -->
-
-<style type="text/css">
-.tabset-dropdown > .nav-tabs {
-  display: inline-table;
-  max-height: 500px;
-  min-height: 44px;
-  overflow-y: auto;
-  background: white;
-  border: 1px solid #ddd;
-  border-radius: 4px;
-}
-
-.tabset-dropdown > .nav-tabs > li.active:before {
-  content: "";
-  font-family: 'Glyphicons Halflings';
-  display: inline-block;
-  padding: 10px;
-  border-right: 1px solid #ddd;
-}
-
-.tabset-dropdown > .nav-tabs.nav-tabs-open > li.active:before {
-  content: "";
-  border: none;
-}
-
-.tabset-dropdown > .nav-tabs.nav-tabs-open:before {
-  content: "";
-  font-family: 'Glyphicons Halflings';
-  display: inline-block;
-  padding: 10px;
-  border-right: 1px solid #ddd;
-}
-
-.tabset-dropdown > .nav-tabs > li.active {
-  display: block;
-}
-
-.tabset-dropdown > .nav-tabs > li > a,
-.tabset-dropdown > .nav-tabs > li > a:focus,
-.tabset-dropdown > .nav-tabs > li > a:hover {
-  border: none;
-  display: inline-block;
-  border-radius: 4px;
-}
-
-.tabset-dropdown > .nav-tabs.nav-tabs-open > li {
-  display: block;
-  float: none;
-}
-
-.tabset-dropdown > .nav-tabs > li {
-  display: none;
-}
-</style>
-
 <script>
 $(document).ready(function () {
   window.buildTabsets("TOC");
 });
-
-$(document).ready(function () {
-  $('.tabset-dropdown > .nav-tabs > li').click(function () {
-    $(this).parent().toggleClass('nav-tabs-open')
-  });
-});
 </script>
 
 <!-- code folding -->
@@ -176,6 +115,7 @@
 
 
 
+
 <div class="fluid-row" id="header">
 
 
@@ -221,7 +161,7 @@ <h3>1.1) Answer</h3>
 </ul>
 <ol style="list-style-type: decimal">
 <li><p>Here I wrote another extention page for Q1 which is analyse the multiple currencies and also models <s>from minutes to</s> daily. You are feel free to browse over <a href="http://rpubs.com/englianhu/binary-Q1E">Binary.com Interview Q1 (Extention)</a> or (<a href="http://rpubs.com/englianhu/316133">Alternate link</a>).</p></li>
-<li><p>Here I also find the optimal arma order for GARCH models as you can refer to <a href="http://rpubs.com/englianhu/binary-Q1FiGJRGARCH">GARCH模型中的<code>ARIMA(p,d,q)</code>参数最优化</a>. <a href="http://rpubs.com/englianhu/binary-Q1-archm">binary.com 面试试题 I - GARCH模型中的<code>ARCH in Mean</code></a> compares the ARCHM with Non-ARCHM models.</p></li>
+<li><p>Here I also find the optimal arma order for GARCH models as you can refer to <a href="http://rpubs.com/englianhu/binary-Q1FiGJRGARCH">GARCH模型中的<code>ARIMA(p,d,q)</code>参数最优化</a>. <a href="http://rpubs.com/englianhu/binary-Q1-archm">binary.com 面试试题 I - GARCH模型中的<code>ARCH in Mean</code></a> compares the ARCHM with previous Non-ARCHM models.</p></li>
 <li><p>You can also refer to <a href="http://rpubs.com/englianhu/binary-Q1Uni-GARCH">binary.com Interview Question I - Comparison of Univariate GARCH Models</a> which compares the prediction accuracy of 14 GARCH models (not completed) and 9 models (mostly completed from 2013-01-01 to 2017-08-30).</p></li>
 </ol>
 <ul>

README.md

@@ -300,9 +300,9 @@ notID %>%
 ```{r warning=FALSE}
 ## timeID which contains 3 prediction models.
 utimeID <- fx %>% 
-  ddply(.(Date, .id), summarize, 
-        n = length(Type)) %>% 
-  dplyr::filter(n == 12) %>% 
+  ddply(.(Date), summarize, 
+        n = n()) %>% 
+  dplyr::filter(n == 84) %>% 
   tbl_df %>% .$Date
 
 fx %<>% dplyr::filter(Date %in% utimeID, !Date %in% ntimeID)
@@ -401,7 +401,7 @@ acc %>%
 
 # 结论
 
-结果证明。目前正在编写着[Q1App2](https://beta.rstudioconnect.com/content/3138/)自动交易应用。“商场如战场”，除了模式最优化以外，程序运作上分秒必争... `microbenchmark`测试效率，之前编写了个[DataCollection](https://beta.rstudioconnect.com/content/3153/)应用采集实时数据以方便之后的高频率交易自动化建模^[不过数据量多就会当机，得继续提升才行。]。欲知更多详情，请参阅[Real Time FXCM](https://github.com/scibrokes/real-time-fxcm)。
+结果证明`pred2`的`archm=FALSE`最为精准。目前正在编写着[Q1App2](https://beta.rstudioconnect.com/content/3138/)自动交易应用。“商场如战场”，除了模式最优化以外，程序运作上分秒必争... `microbenchmark`测试效率，之前编写了个[DataCollection](https://beta.rstudioconnect.com/content/3153/)应用采集实时数据以方便之后的高频率交易自动化建模^[不过数据量多就会当机，得继续提升才行。]。欲知更多详情，请参阅[Real Time FXCM](https://github.com/scibrokes/real-time-fxcm)。
 
 # 附录
 

binary-Q1-archm.Rmd

@@ -638,7 +638,7 @@ The new dshw() function implements *Taylor’s (2003)* double-seasonal Holt-Wint
 
 *Source : Major changes to the forecast package*
 
-Now we start modelling harmonics model (which is using `xreg`).
+[Forecasting Daily Data with Multiple Seasonality in R](http://www.dbenson.co.uk/Rparts/subpages/forecastR/) provides the example for seasonal modelling. Now we start modelling harmonics model (which is using `xreg`).
 
 #### Model 1