alternative cash flow vector code rstudio

#ALTERNATIVE CASH FLOW VECTOR CODE RSTUDIO FULL#

For example, once you learn to use the predict function, when you load a new package, that function may gain new abilities to deal with model objects that are computed specifically within the new package. However, it does mean that you have fewer commands to learn. This means you can’t simply read a help file, understand it, and you’re done learning that function forever. You have to know to look for help on “class” to find that.Īnother confusing aspect to R’s help files stems from R’s ability to add new features to existing functions as you load add-on packages. The help files will tell you more about “methods” but not “classes”. It is a generic function which means that new printing methods can be easily added for new classes.” The reader is left to wonder what “invisible” output looks like and what methods and classes are. The R help file for its print function says, “print prints its argument and returns it invisibly (via invisible(x)). The SAS help file for its print procedure says that it “Prints observations in a SAS data set using some or all of the variables.” Clear enough. However, they’re definitely not written for beginners! My favorite example of this is the help file for one of the first commands that beginners learn: print. R’s help files are often thorough and usually contain many working examples. In addition, the existence of multiple GUIs means that the volunteer effort that is spent on them is spread across many versions instead of just one.

You can read about the many available in this comparison article, but with so many to choose from, it further complicates the learning process. However unlike many others, it does not offer a standard GUI to help non-programmers do analyses.

#ALTERNATIVE CASH FLOW VECTOR CODE RSTUDIO FULL#

Like most other packages, R’s full power is only accessible through programming. Too Many Graphical User Interfaces (GUIs) However, add-on packages help make the easy things easy as well. As many have said, R makes easy things hard, and hard things easy. By listing these, I hope R beginners will be forewarned, will become aware that many of these problems come with benefits, and may consider the solutions offered by the add-on packages that I suggest. This is the approach I use in my books, R for SAS and SPSS Users and R for Stata Users, as well as in the workshops that are based on those books.īelow is a list of complaints about R that I commonly hear from people taking my R workshops. Training and documentation that leverages your existing knowledge and which points out where your previous knowledge is likely to mislead you can save much frustration. If you have experience with other data science tools, you may at first find R very alien. And, as with any software, some is due to design decisions that, in hindsight, could have been better. Some is an unavoidable byproduct of its extreme power and flexibility. Some of that is due to the fact that it is radically different from other analytics software. R has a reputation of being hard to learn.

Alternative cash flow vector code rstudio