How to install the JSON extension for Ubuntu 16.04?
Adding the PHP json extension
When I try to start Runescape I get an error message that says: CLassNotFoundException and lists Rs2Applet.class. How do I fix this so I can play? From official :     Due to a head injury, Cyclops is unable to shut off his optic blasts   at will and must therefore wear ruby quartz lenses to block the beams.   From the same page:     Cyclops possesses the mutant ability to project a beam of heatless   ruby-colored concussive force from his eyes, which act as   inter-dimensional apertures between this universe and another.   When his eyes are always blocked by ruby-colored beam of concussive force, how does he see? If HTML, CSS, and Javascript are client-side, why are they components of a PHP file? Why is the mean function in Gaussian Process uninteresting? echo "#!" fails -- "event not found" Solving a implicit, recursive function Assuming $F(0,0)=0$, can I solve $F(F(x,y),y)=0$ for $y=f(x)$ near $(0,0).$ Stack Exchange Android app keeps replaying notifications Version of the app: 1.0.51. (It is up to date at the time of writing according to Google Play.)  This started happening after the network problem that happened earlier this morning. Both my tablet and my phone are popping up notifications for events (comments, and probably edits too) that happened prior to the network issue. I had received notifications for these events already and had already cleared them before the network issue happened.  The repeated notifications do not show up in the bar displayed at the top of the Stack Exchange sites. In other words, I get notified again in Android but do not get notified again on the SE web sites. Does the sequence $\{\sin^n(n)\}$ converge?   Does the series $\sum\limits_{n=1}^\infty \sin^n(n)$ converge? prove $\sqrt{a_n b_n}$ and $\frac{1}{2}(a_n+b_n)$ have same limit Bezout's identity in $F[x]$ Let $F$ be a field and $F[x]$ a polynomial ring. Let $p(x)$ be an irreducible polynomial.  Show that $\gcd(p(x),q(x)) = 1\Longrightarrow \exists r(x),s(x)$ such that $r(x)p(x)+s(x)q(x) = 1$.  I know the proof for Bezout's identity for , but this proof uses the notion of absolute value, which cannot be applied to a polynomial ring.   I am thinking about a way to prove the statement: Use the Euclidean algorithm to compute $\gcd(p(x),q(x))$ and show that the result is $1$, and somehow go backwards to obtain $r(x)p(x)+s(x)q(x) = 1$, but it is a bit messy, and I'm not yet able to see it completely.  Please offer some help. If you have some other methods, that would be great, too. How do I move my website to a new server without interruption to email? Are submodules of finitely generated free modules always free? I don't believe it's true that all submodules of a finitely generated free module are free just based on results from google. Is there a canonical simple example of a finitely generated free module with a submodule that is not free? What is the difference between would and will in the following examples?        How would you use this word in a sentence?     How will you use this word in a sentence? How to completely uninstall and remove QGIS 2.8.1 on Windows Vista? I want to uninstall and completely remove QGIS installation from my computer(windows vista). I have uninstalled it and when i try to reinstall it says it is already installed on the system. Is the word "management" singular or plural? Possible Duplicate:          Which one of the following is correct?     Management gets its ideas from its employees.   Management gets their ideas from their employees. Shrink the database only up to its initial size which is set after creating database In SQL server every database has a property Initial Size (MB) which can be seen in properties of database in SSMS. By default it will be 3 MB for mdf and 1 MB for ldf file.  So now if create a new database then it will be set to default size(i.e 3 MB for mdf and 1 mb for ldf file). But after creating the database  I change the initial size to some other value say For mdf 10 MB and ldf 5 MB.(In real-time some database administrator may want to change initial after creating database)  But now if shrink the database it will shrink beyond the initial size I have set after creation(consider that no data is there in database otherwise it will shrink to its actual content size). It will shrink till the initial size it had during creation of database(i.e 3mb for mdf and 1 mb for ldf). I was expecting to shrink till the initial size which I have set(i.e 10 mb for mdf and 5mb for ldf). Can it be possible to do? If possible then how?  In some article i saw like dbcc SHRINKFILE can be used to shrink beyond initial size and dbcc SHRINKDATABASE cannot shrink beyond initial size. But I want to shrink only till the initial size to which I have set.  Note: I know that shrink is bad and should not be done.But I want to know how it can be done? If sql server considers only the initial size set during creation of database then what is the use of setting the initial size after creating database?  EDIT:  From microsoft shrink related article: Using DBCC SHRINKDATABASE you can not shrink database below its initial size.  My question is Can I change the initial size of existing database itself?  EDIT:  I have about 5 sql server instance. All the database where created with default size of 3 mb for data and 1 mb for log(about 3 years back). Now all the databases are in the range of 100-1000 mb. I wont shrink the database normally as it is not good practice. But some database grow more than 10 GB(mdf file itself as i insert so much data in it). So when database is large I will shift unimportant and old contents from this database to another server as it is not required in that server for me. So that database size reduces from 10 GB to 1 GB. Now the remaining 9 Gb left unused. Now I  want to specify database size to be reduced to 2 GB so that i will get 1 GB free space(Also 2 Gb is the ideal size for this database), Which can be used to avoid autogrowth till next 1 Gb of data is filled. Also i have set 100 MB auto-growth for this kind of large database which has more writes. So instead of specifying size as 2 GB in shrinkfile command,if it was possible to change initial size to 2 GB (which shrink considers) then it would have been better. During this database creation there was no plan about size ,autogroth etc. As it was created about 3 years back. Now i am planning to set autogrowth etc. I cant again create new database with new initial size and shift data. So I was asking whether I can change the Initial size for existing database? Suppose I have a dataframe consisting of six time series. In this dataframe, some observations are missing, meaning at some timepoints all time series contain a NA-value. In R, one possible imputation package that can be used to impute time series data is Amelia. However, this package does not work for observations that are completely missing. Are there other ways to impute my data? For what it's worth, the amount of missing observations is less than 20% of all observations. I came across the following question:     If 3 boys can paint a fence in 2 days what part of the job can     be completed by two boys in 1 day?   The answer to this problem is $\frac13$.  I can't manage to tackle this problem. Could anyone tell me what would be the quickest way to solve this problem (This question is a standardized test based question). Any help would be appreciated. Why is it possible to get significant F statistic (p<.001) but non-significant regressor t-tests? In a multiple linear regression, why is it possible to have a highly significant F statistic (p&lt;.001) but have very high p-values on all the regressor's t tests?  In my model, there are 10 regressors. One has a p-value of 0.1 and the rest are above 0.9    For dealing with this problem see the . I'm trying to understand at a deeper level the ubiquity of log-likelihood (and perhaps more generally log-probability) in statistics and probability theory.  Log-probabilities show up all over the place: we usually work with the log-likelihood for analysis (e.g. for maximization), the Fisher information is defined in terms of the second derivative of the log-likelihood, entropy is an expected log-probability, Kullback-Liebler divergence involves log-probabilities, the expected diviance is an expected log-likelihood, etc.    Now I appreciate the many practical and convenient reasons.  Many common and useful pdfs are from exponential families, which leads to elegantly simplified terms when log-transformed.  Sums are easier to work with than products (esp for differentiating).  Log-probs have a great floating point advantage over straight probs.  Log-transforming a pdf often converts a non-concave function into a concave function.  But what is the theoretical reason/justification/motivation for log-probs?  As an example of my perplexity, consider the Fisher information (FI).  The usual explanation for intuiting the FI is that the second derivative of the log-likelihood tells us how "peaked" the log-likehood is:  a highly peaked log-likelihood means the MLE is well-specified and we are relatively sure of its value, while a nearly flat log-likehood (low curvature) means many different parameter values are nearly as good (in terms of the log-likelihood) as the MLE, so our MLE is more uncertain.   This is all well-and-good, but isn't it more natural to just find the curvature of the likelihood function itself (NOT log-transformed)?  At first glance the emphasis on the log-transform seems arbitrary and wrong.  Surely we are more interested in the curvature of the actual likelihood function.  What was Fisher's motivation for working with the score function and the Hessian of the log-likelihood instead?  Is the answer simply that, in the end, we have nice results from the log-likelihood asymptotically? E.g., Cramer-Rao and normality of the MLE/posterior.  Or is there a deeper reason?