Negate line in LOG smoothly

Aug 6th, 2022
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How to Negate line in LOG

4.8 out of 5
46 votes

hello in this simple tutorial I will show how to take lot of a variable data contain negative values but number I have a variable volume I will see whether it is any negative rate with or not then well just create their summary statistics I can see that the minimum value is minus 1 0 0 raised to the power 8 and I will just copy them that I have been using my code generator block off the abbreviated portfolio which can take negative value so I will just create a simple loss of a portfolio with the negative values and then I will just type this in one formula and aid of the ranging thing I have copied from the minimum so I would just ensure later I have to kill portfolio by adding a number that is greater than this minimum number and negatively so I will just for example we use a number that is positive and it is till then to point C 1 so that is exactly if I ate two point eight zero this raise this it wont become positive so because I am aiming the same to the same variable but then j

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In other words, the only numbers you can plug into a log function are positive numbers. Negative numbers, and the number 0, arent acceptable arguments to plug into a logarithm, but why? The reason has more to do with the base of the logarithm than with the argument of the logarithm.
log (1/a) = -log a means that the logarithm of 1 divided by some number is equal to the negative logarithm of that number. (This is the exactly the opposite of the rule governing exponents where a number raised to a negative number is equal to 1 divided by that number raised to that power.)
The logarithm of a negative number is obtained by multiplying its magnitude with -1.
The argument of a log function can only take positive arguments. In other words, the only numbers you can plug into a log function are positive numbers.
The logarithm of a negative number is obtained by multiplying its magnitude with -1.
A common technique for handling negative values is to add a constant value to the data prior to applying the log transform. The transformation is therefore log(Y+a) where a is the constant. Some people like to choose a so that min(Y+a) is a very small positive number (like 0.001). Others choose a so that min(Y+a) = 1.

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