1) Sage seems unable to reduce `erf(x) == erf(y)` to `x == y`. How can I help
this along?
solve(erf(x) == erf(y), x)[0].simplify_full()
Actual output: x == inverse_erf(erf(y))
Expected output: x == y
I had expected that sage would trivially reduce `inverse_erf(erf(y))` to `y`.
2) This output references 'inverse_erf', which doesn't seem to be importable t
from anywhere in sage. Am I correct?
---
My concrete problem is re-deriving the formula for the normal-distribution cdf.
I get a good solution from sage, but fail in showing that it's equivalent to a
known solution because:
var('x sigma mu')
assume(sigma > 0)
eq3 = (-erf((sqrt(2)*mu - sqrt(2)*x)/(2*sigma)) == -erf((sqrt(2)*(mu -
x))/(2*sigma)))
bool(eq3)
Actual output: False
Expected output: True
However this quite similar formula works fine:
eq3 = (-erf(sqrt(2)*mu - sqrt(2)*x) == -erf(sqrt(2)*(mu - x)))
bool(eq3)
Output: True
---
Include:
Platform (CPU) -- x86_64
Operating System -- Ubuntu 13.10
Exact version of Sage (command: "version()") -- 'Sage Version 5.13, Release
Date: 2013-12-15'
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