[Eventstudies-commits] r407 - pkg/inst/tests

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Fri Mar 13 08:17:59 CET 2015


Author: chiraganand
Date: 2015-03-13 08:17:59 +0100 (Fri, 13 Mar 2015)
New Revision: 407

Modified:
   pkg/inst/tests/test_compilation.txt
Log:
Added markers for tests which need to be coded for this version.

Modified: pkg/inst/tests/test_compilation.txt
===================================================================
--- pkg/inst/tests/test_compilation.txt	2015-03-12 20:31:22 UTC (rev 406)
+++ pkg/inst/tests/test_compilation.txt	2015-03-13 07:17:59 UTC (rev 407)
@@ -17,8 +17,8 @@
       	* zero
 	* +Inf
       	* -Inf
-	* Values greater than the no. of rows in dataframe StockPriceReturns
-   b) Check for following when zoo object with firm data and dates as index is a univariate series:
+>	* Values greater than the no. of rows in dataframe StockPriceReturns
+>   b) Check for following when zoo object with firm data and dates as index is a univariate series:
       # If univariate series is input as vector (not matrix), then the function fails.
    c) Check for following values for z (zoo object):
       # Extreme values:
@@ -31,40 +31,40 @@
 ****************** Models ********************
 
 2. Function marketModel
-   a) Check whether: # of rows in df(firm returns) = # of rows in df(market returns) 
+>   a) Check whether: # of rows in df(firm returns) = # of rows in df(market returns) 
    b) Check for extreme values of no. of rows and columns i.e. 1 row or 1 col in dataset
-   c) Check for residuals = TRUE (whether data is in returns or price format)
-   d) Check for class of arguments 
+>   c) Check for residuals = TRUE (whether data is in returns or price format)
+>   d) Check for class of arguments 
 
 3. Function excessReturn
-   a) Check whether: # of rows in df(firm returns) = # of rows in df(market returns)
+>   a) Check whether: # of rows in df(firm returns) = # of rows in df(market returns)
    b) Check for extreme values of no. of rows and columns i.e. 1 row or 1 col in dataset   
-   c) Check for class of arguments   
+>   c) Check for class of arguments   
  
 4. Function lmAMM
-   a) Check for whether X is the output of makeX or not (read makeX manual)
-   b) Check for other logical arguments (those with TRUE/FALSE)
+>   a) Check for whether X is the output of makeX or not (read makeX manual)
+>   b) Check for other logical arguments (those with TRUE/FALSE)
 
 5. Function None
-   a) Check that no model arguments should be specified
+>   a) Check that no model arguments should be specified
 
 
 ************** Remap functions **************
 
 6. Function remap.cumsum
-   a) Check for is.pc = TRUE (whether data is in percentage)
+>   a) Check for is.pc = TRUE (whether data is in percentage)
    b) Check for following values of base:
-      # Normal values:
+>      # Normal values:
         * 0
         * 100
       # Extreme values:
 	* -Inf
 	* Inf  
 7. Function remap.cumprod
-   a) Check for is.pc = TRUE (whether data is in percentage)
-   b) Check for is.pc = TRUE (whether data is in returns or price format)
+>   a) Check for is.pc = TRUE (whether data is in percentage)
+>   b) Check for is.pc = TRUE (whether data is in returns or price format)
    c) Check for following values of base:
-      # Normal values:
+>      # Normal values:
         * 0
         * 100
       # Extreme values:
@@ -74,7 +74,7 @@
 ************* Inference procedures ***********
 
 8. Function inference.bootstrap
-   a) Check for following values of boot.run:
+>   a) Check for following values of boot.run:
       # Normal values:
         * 1000
 	* 10  
@@ -84,18 +84,18 @@
    b) Check for following values of es.w:
       # Extreme values:
 	* Only one row in zoo object, es.w (i.e. only one observation for each firm which is corresponding to event date)  
-	* Only one column in zoo object, es.w (i.e. data input is only for one firm)
+>	* Only one column in zoo object, es.w (i.e. data input is only for one firm)
 
 10. Function inference.wilcox
    a) Check for following values of prob:
-      # Normal values:
+>      # Normal values:
         * .10
       # Extreme values:
 	* Any value less than 0 and greater than 1
    b) Check for following values of es.w:
       # Extreme values:
 	* Only one row in zoo object, es.w (i.e. only one observation for each firm which is corresponding to event date)  
-	* Only one column in zoo object, es.w  (i.e. data input is only for one firm)
+>	* Only one column in zoo object, es.w  (i.e. data input is only for one firm)
 
 
 ************************************************************************************************************
@@ -103,20 +103,20 @@
 II. TESTS FOR FUNCTIONALITY
 
 1. Function phys2eventime 
-   a) Check for list components returned by the function
+ >  a) Check for list components returned by the function
       * Check for the structure of `z.e'. It should not be a transpose
    (of the format in which it goes in inference.bootstrap())
-   b) Check for firm selected should not have NA in data for defined width
-   c) Check for class of arguments
-   d) Check for if the function handles following data discrepancies in events:
+>   b) Check for firm selected should not have NA in data for defined width
+>   c) Check for class of arguments
+>   d) Check for if the function handles following data discrepancies in events:
       * Missing dates in eventlist 
       * Missing firm in eventlist  
-   e) When zoo object with firm data and dates as index is a univariate series, 
+>   e) When zoo object with firm data and dates as index is a univariate series, 
       function must work if its a matrix of one column (i.e. only one
    observation for each firm which is corresponding to event date), or
    if it is a matrix of one column (i.e. data input is only for one
    firm).
-   f) Check for only one observation in data frame, event.list
+>   f) Check for only one observation in data frame, event.list
    (i.e. only one firm has an observed event)
       
 
@@ -129,7 +129,7 @@
    a) Check with small sample data whether the result is correct or not.
    
 4. Function lmaMM
-   a) Check for class of arguments
+L   a) Check for class of arguments
    b) Check the working and results of regression analysis manually: difficult @leave this for now
    @ remind to come up with test cases for lmAMM
 
@@ -137,17 +137,17 @@
 
 ************** Remap functions **************
 6. Function remap.cumsum
-   a) Cumulate by summing and tally
+>   a) Cumulate by summing and tally
 
 7. Function remap.cumprod
-   a) Cumulate by multiplying and tally
+>   a) Cumulate by multiplying and tally
 
 ************* Inference procedures ***********
 
 8. Function inference.bootstrap @think and read
-   a) Check the structure of es.w given as argument (it should be zoo
+>   a) Check the structure of es.w given as argument (it should be zoo
    object indexed by event time and the `z.e' component of the list
-   returned by the ‘phys2eventtime’ function.
+   returned by the "phys2eventtime" function.
    * Check the structure of es$z.e given as argument
 
 9. Function inference.wilcox   @think and read
@@ -157,19 +157,19 @@
 III. TESTS FOR AGGREGATE FUNCTION (eventstudy)
 
 10. Check the following for argument, event.window:
-      # Normal values:
+>      # Normal values:
         * Any value less than no. of rows of firm.returns and greater than zero
       # Extreme values:
 	* 0
 	* Inf/ -Inf
 	* Any value greater than no. of rows of firm.returns and less than zero
-   b) Check that event.window does not overlap with estimation window (i.e. firm returns 
+>   b) Check that event.window does not overlap with estimation window (i.e. firm returns 
       used to estimate market returns through any of the described models.
    c) 
 ***************** Models *********************
 
 10. Check the function for all the models using small data sets:
-    a) Check for the argument, type: by default, model type (argument in eventstudy 
+>    a) Check for the argument, type: by default, model type (argument in eventstudy 
        function) should be market model, else specify the type as any of the following:
        # none
        # lmAMM
@@ -178,13 +178,13 @@
 ***************** Remap functions ************
 
 11. Check the function for logical argument to.remap (taking values TRUE/ FALSE):
-    a) for cumsum
-    b) for cumprod
+>    a) for cumsum
+>    b) for cumprod
 
 ************* Inference procedures ***********
 
-12. Check the function for logical argument inference (taking values TRUE/ FALSE):
-13. Check the function for the argument inference.strategy taking following values:
+> 12. Check the function for logical argument inference (taking values TRUE/ FALSE):
+> 13. Check the function for the argument inference.strategy taking following values:
     a) bootstrap
     b) wilcoxin
 



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