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Frank Raulf
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Frank Raulf posted a blog post

Omitted Variables in Linear Regressions

The importance of completeness of linear regressions is an often-discussed issue. By leaving out relevant variables the coefficients might be inconsistent.But why on earth?! Assuming a linear complete model of the form:z = a + bx + cy + ε.Where z is supposed to be dependent, x and y are independent and ε is the error term.Now we drop y to check which terms are affected. By reducing one dimension we transform a linear hyperplane to a linear line. In the initial three-dimensional space this…See More
4 hours ago
Frank Raulf's blog post was featured

Omitted Variables in Linear Regressions

The importance of completeness of linear regressions is an often-discussed issue. By leaving out relevant variables the coefficients might be inconsistent.But why on earth?! Assuming a linear complete model of the form:z = a + bx + cy + ε.Where z is supposed to be dependent, x and y are independent and ε is the error term.Now we drop y to check which terms are affected. By reducing one dimension we transform a linear hyperplane to a linear line. In the initial three-dimensional space this…See More
Thursday
Daren Scot Wilson liked Frank Raulf's blog post Loop-Runtime Comparison R, RCPP, Python
Sep 4
Frank Raulf posted blog posts
Sep 1
Frank Raulf's blog post was featured

Loop-Runtime Comparison R, RCPP, Python

The positive reactions on my last post: “Different kinds of loops in R” lead me to compare some different versions of loops in R, RCPP (C++ integration of R). To see a bigger picture, I apply the Python for-loop additionally. The comparison focuses on the runtime for non-costly tasks with different numbers of iterations. For comparison purpose I create vectors in the form of (R syntax):Vector <- 1:kk = (1.000, 100.000, 1.000.000) The task is to calculate a vector of (k-1) growth rates. I use…See More
Sep 1
Frank Raulf liked Frank Raulf's blog post Different kinds of loops in R.
Aug 15
Chana VanNice liked Frank Raulf's blog post Different kinds of loops in R.
Aug 15
Frank Raulf posted blog posts
Aug 15
Frank Raulf's blog post was featured

Different kinds of loops in R.

Normally, it is better to avoid loops in R. But for highly individual tasks a vectorization is not always possible. Hence, a loop is needed – if the problem is decomposable.Which different kinds of loops exist in R and which one to use in which situation?In each programming language, for- and while-loops (sometimes until-loops) exist. These loops are sequential and not that fast – in R.for(i in x){task} i=ywhile(i<=x){taski=i+1} Even for prototyping sometimes too slow.But how to improve…See More
Aug 15
Frank Raulf posted a blog post

Data Quality Maintenance

How to implement supporting data-quality-maintenance-systems using AI? How to find out which method performs best? Is it possible to further improve the results? How to take advantage of complementary human-machine-perception? This is an example of a successful implementation. Read my article on this topic,…See More
Aug 4
Frank Raulf's blog post was featured

Data Quality Maintenance

How to implement supporting data-quality-maintenance-systems using AI? How to find out which method performs best? Is it possible to further improve the results? How to take advantage of complementary human-machine-perception? This is an example of a successful implementation. Read my article on this topic,…See More
Aug 4
Frank Raulf replied to Capri Granville's discussion Is it better to overpredict, or underpredict?
"In my opinion it depends on the purpose of the prediction but that is always a trade-off. In the case of flu prediction I am not sure whether there are legal risks but the quality of the prediction is definitely lower. Hence, the weather prediction…"
Jun 4

Profile Information

Field of Expertise
Data Science, Machine Learning, AI, Business Analytics, Deep Learning, BI
Professional Status
Technical
Years of Experience:
6
Your Company:
Deutsche Bundesbank
Industry:
Banking
Your Job Title:
Senior Data Scientist
How did you find out about DataScienceCentral?
LinkedIn
Interests:
Contributing, Networking, New venture

Frank Raulf's Blog

Omitted Variables in Linear Regressions

Posted on November 13, 2019 at 2:00am 0 Comments

The importance of completeness of linear regressions is an often-discussed issue. By leaving out relevant variables the coefficients might be inconsistent.

But why on earth?! 

Assuming a linear complete model of the form:

z = a + bx + cy + ε.

Where z is supposed to be dependent, x and y are independent and ε is the error term.

Now we drop y to check…

Continue

Loop-Runtime Comparison R, RCPP, Python

Posted on September 1, 2019 at 4:30am 0 Comments

The positive reactions on my last post: “Different kinds of loops in R” lead me to compare some different versions of loops in R, RCPP (C++ integration of R). To see a bigger picture, I apply the Python for-loop additionally. The comparison focuses on the runtime for non-costly tasks with different numbers of iterations. For comparison purpose I create vectors in the form of (R syntax):

Vector <- 1:k

k = (1.000, 100.000, 1.000.000)

 

The task is to…

Continue

Different kinds of loops in R.

Posted on August 12, 2019 at 12:30am 0 Comments

Normally, it is better to avoid loops in R. But for highly individual tasks a vectorization is not always possible. Hence, a loop is needed – if the problem is decomposable.

Which different kinds of loops exist in R and which one to use in which situation?

In each programming language, for- and while-loops (sometimes until-loops) exist. These loops are sequential and not that fast – in R.

for(i in…

Continue

Data Quality Maintenance

Posted on August 2, 2019 at 12:00am 0 Comments

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