How to replace missing points in a data set?

I want to write a function in R that receives any data set as input, such that the data set has some missing points (NA). Now I want to use mean function to replace some numbers/values for missing points (NA) in the data set. What I am thinking is a function like this:

x<function(data,type=c("mean", lag=2))

Indeed, it should compute the mean of the two numbers later and two numbers before of the missing point (because I considered lag as 2 in the function). For example, if the missing point is in place 12th then the function should compute the mean of the numbers in places 10th, 11th, 13th, and 14th and substitute the result for the missing point at place 12th. In particular cases, for example, if the missing point is in the last place, and we do not have two numbers later, the function should compute the mean of all the data of the corresponding column and substitute for the missing point. Here I give an example to make it clear. Consider the following data set:

3  7 8 0  8  12 2
5  8 9 2  8  9  1
1  2 4 5  0  6  7
5  6 0 NA 3  9  10
7  2 3 6  11 14 2
4  8 7 4  5  3  NA

In the above data set, the first NA should be replaced with the mean of numbers 2, 5 (two data before), and 6 and 4 (two data after) which is (2+5+6+4)/4 is equal to 17/4. And the last NA should be replaced with the mean of the last column which is (2+1+7+10+2)/5 is equal to 22/5.

My question is how can I add some codes (if, if-else, or other loops) to the above function to make a complete function to satisfy the above explanations.