# What is an equi-depth partition of the data?

In the paper Outlier Detection for High Dimensional Data at the beginning of section 1.3 Is written:

Each attribute of the data is divided into $\phi$ equi-depth ranges. Thus, each range contains a fraction f = 1 /$\phi$ of the records.

What does it mean? Can you write an example?
If the data is $n \times p$ will I get $\phi$ matrix of size $\dfrac{n}{\phi}\times p$?

• It seems to me the second sentence of the quotation includes the answer to the question. – whuber Aug 20 '14 at 13:30
• After a while my understanding is that each variables have to be split in $\phi$ parts independently from the others. – Donbeo Aug 20 '14 at 13:54