I would like to clarify how  can/should be used in practice, and how to interpret the statistical significance given by the test.  Also, I would like to fill this table with things like "we don't know" or if we know something, what do we know (It will for sure not be causality, but maybe something else?).                          X Granger cause Y sig.   X Granger cause Y not  Y Granger cause X sig.                     ...                     ...  Y Granger cause X not                      ...                     ...
I'm trying to educate myself on Granger Causality. I've read the posts on this site and several good articles online.  I also came across a very helpful tool, the , that allows you to enter your time series and calculate the Granger Stats.  Below, is the output from the sample data included on the site. I have also taken a crack at interpreting the results.   My Questions:     Is my interpretation directionally correct?   What key insights have I overlooked?   Also what is the meaning and interpretation of the CCF charts?  (I'm assuming CCF is cross correlation.)     Here are the results and plots that I have interpreted:  Summary of computational transaction Raw Input   view raw input (R code) Raw Output  view raw output of R engine Computing time  2 seconds R Server    'Herman Ole Andreas Wold' @ wold.wessa.net  Granger Causality Test: Y = f(X) Model   Res.DF  Diff. DF    F   p-value Complete model  356          Reduced model   357 -1  17.9144959720894    2.94360540545316e-05  Granger Causality Test: X = f(Y) Model   Res.DF  Diff. DF    F   p-value Complete model  356          Reduced model   357 -1  0.0929541667364279  0.760632773377753       My interpretation:    Test was based upon 357 data points and was performed with a lag value of 1 The p-value of 0.0000294 means I can reject the null hypothesis that x does not cause y for the Y = f(x). The p-value of .76 allows me to accept the null for X = f(Y) The fact that first hypothesis was rejected and second accepted is a good thing  I'm a little rusty on my F-test so I don't really have anything to say on this for now. I'm also not sure how to interpret the CCF graph.   I really appreciate it if any of you who are well versed with Granger-causality could let me know if I'm interpeting this correctly and also fill in some of the blanks.   Thanks for your help.
What is the reason the log transformation is used with right-skewed distributions? I once heard that      log transformation is the most popular one for right-skewed distributions in linear regression or quantile regression   I would like to know is there any reason underlying this statement? Why is the log transformation suitable for a right-skewed distribution?   How about a left-skewed distribution? If I squeeze something really hard, will it ever become two-dimensional? Let $(M,d)$ be a metric space, and $A\subset M$. By definition, $A$ is said to be compact if every open cover of $A$ contains a finite subcover.  What is wrong with saying that, in $\mathbb{R}$, if $I=(0,1)$, we can choose $G=\{(0,\frac{3}{4}), (\frac{1}{4}, 1)\}$, which satisfies $I \subset \bigcup_{U\in G} U$, but we can't extract a finite subcover, so $I$ is not compact. Is $G$ a finite subcover of $G$, so it is not a valid cover for proving this? I would take $\cup_{n\in\mathbb{N}} (\frac{1}{n},1)$ in order to prove this, can we conclude that every open cover is necessarily a infinite union of open sets $\neq \emptyset$? How do I configure my DNS settings in Ubuntu server? How to exit from an application which doesn’t exit on press back button? How to fill down in Numbers without dragging? parsing XML file gets UnicodeEncodeError (ElementTree) / ValueError (lxml) I'm trying to use a mask to hide a part of a render layer, so that when the render layer is shown over a movie, some parts in the movie will appear to be in front of the render layer.  For example, assume I want to add a box to this image, so that it would look like it's behind the person:    I created the following simple object:    If I render the object, it looks great - the object is solid, everything else is transparent (I didn't use any 'sky'):     Now I create a mask to describe the standing person (or at least the part that would otherwise be covered by the box):    What I want now is to create a "hole" in the rendered box, so that when I use Alpha-over, the box look as if it's behind the person, but I can't find an easy way to do that. My first guess was to use 'Set alpha' to apply the mask (inverted) as an alpha for the rendered layer, but this doesn't look good:    The mask did create a "hole" where it should, but now all the other pixels are not transparent. How can I "retain" the transparent pixels while setting more pixels to be transparent based on the mask (use it as a matte)?  Note: I can do this with (I'm ashamed to say) some math work on the alpha channel, but it just doesn't seem right:    Thanks, and sorry for the [oh so] long question. Why does Kylo Ren's lightsaber look different from normal lightsabers? I'm trying to determine if there is a best practice for typesetting the "evaluated at" bar for derivatives. The three possibilities I'm thinking of are shown in the code excerpt below:  \begin{gather*} 5 + \frac{df}{dt} \Bigr\rvert_{t = 0} \\ 5 + \frac{df}{dt} \biggr\rvert_{t = 0} \\ 5 + \left. \frac{df}{dt} \right\rvert_{t = 0} \\ \end{gather*}     The \Bigr option doesn't quite reach the top and bottom of the fraction. The \biggr option overshoots the top and bottom of the fraction by a little bit. And the \left...\right option has the same height as the \biggr option, but it introduces a little extra space between the + and the fraction. I'm having trouble deciding between these options. Is there a best practice for typesetting this? What is __init__.py for? What is __init__.py for in a Python source directory? In bash, read after a pipe is not setting values With ksh I'm using read as a convenient way to separate values: $ echo 1 2 3 4 5 | read a b dump $ echo $b $a  2 1 $  But it fails in Bash: $ echo 1 2 3 4 5 | read a b dump $ echo $b $a     $  I didn't find a reason in the man page why it fails, any idea? Bluetooth headset never gives me sound options How to know current name of the database in Django? I have a Python script which I would like to execute at every startup. I can run it by adding this to the startup applications:  python3 /path/to/script.py   That works, but it doesn't open a terminal window, so I can't see the program's output. How could I make it open a terminal window and execute the script in there?  Note: I get the window to stay open with input(' ') at the end of the Python script. Thanks! How do I escape a single quote in SQL Server? Is there anybody who can help me show the following?      $$ \sum_{x=0}^{n-1} \cos\left(k +x{2\pi\over n}\right) =0  \qquad\hbox{and}\qquad  \sum_{x=0}^{n-1} \sin\left(k +x{2\pi\over n}\right) =0 $$   I can only prove this claim for the sine expression when $k=0$, by grouping the output values such that they all cancel out (for both $n$ even and odd). I have thought about using complex numbers in exponential form to prove it, but I can't do it ... :P   I would really appreciate an algerbraic proof. Can I see my active diplomatic deals in Civ 6? When making deals with AI I'm having a hard time assessing if I'm already trading for the resource or not. Is there a way I can see my currently active deals or deal history?  If not, is there a way I can see which resources I am currently importing? I want to communicate between several computers on my network (static Ethernet), through SSH. In order to do that I need to run ssh-add every time I log in on a specific machine, how can I do it so that it's set up once and it doesn't ask me for the passphrase every time I log in or reboot my machine?  I know that there is a way that you should add some lines to the bash_profile file, but I still need to type the password every time I reboot/log in to a specific machine.  if [ -z "$SSH_AUTH_SOCK" ] ; then     eval `ssh-agent -s`     ssh-add fi Calendar link to different page views