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sestim

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The answer SESTIM has 0 possible clue(s) in existing crosswords.

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The word SESTIM is NOT valid in any word game. (Sorry, you cannot play SESTIM in Scrabble, Words With Friends etc)

There are 6 letters in SESTIM ( E1I1M3S1T1 )

To search all scrabble anagrams of SESTIM, to go: SESTIM?

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Scrabble results that can be created with an extra letter added to SESTIM

BEMISTS SAMITES TSIMMES THEISMS TAMISES STYMIES STIMIES SOMITES SMITERS KISMETS MITOSES MISTERS MISSTEP MISSETS MISSENT MISSEAT MISEATS METISSE MITISES

6 letters out of SESTIM

MISSET SMITES STIMES TMESIS

5 letters out of SESTIM

EMITS ITEMS METIS MISES MISTS MITES SEISM SEMIS SITES SMITE STEMS STIES STIME TIMES

4 letters out of SESTIM

EMIT ISMS ITEM MESS MISE MISS MIST MITE SEIS SEMI SETS SIMS SITE SITS SMIT STEM TIES TIME

3 letters out of SESTIM

EMS ESS ISM ITS MET MIS SEI SET SIM SIS SIT TIE TIS

2 letters out of SESTIM

EM ES ET IS IT ME MI SI TI

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Definitions of sestim in various dictionaries:

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Keep reading for additional results and analysis below.

Sestim might refer to
The goal of S-estimators is to have a simple high-breakdown regression estimator, which share the flexibility and nice asymptotic properties of M-estimators. The name "S-estimators" was chosen as they are based on estimators of scale.
* We will consider estimators of scale defined by a function
*
*
*
* ρ
*
*
* {\displaystyle \rho }
* , which satisfy
* R1 -
*
*
*
* ρ
*
*
* {\displaystyle \rho }
* is symmetric, continuously differentiable and
*
*
*
* ρ
* (
* 0
* )
* =
* 0
*
*
* {\displaystyle \rho (0)=0}
* .
* R2 - there exists
*
*
*
* c
* >
* 0
*
*
* {\displaystyle c>0}
* such that
*
*
*
* ρ
*
*
* {\displaystyle \rho }
* is strictly increasing on
*
*
*
* [
* c
* ,
* ∞
* [
*
*
* {\displaystyle [c,\infty [}
*
* For any sample
*
*
*
* {
*
* r
*
* 1
*
*
* ,
* .
* .
* .
* ,
*
* r
*
* n
*
*
* }
*
*
* {\displaystyle \{r_{1},...,r_{n}\}}
* of real numbers, we define the scale estimate
*
*
*
* s
* (
*
* r
*
* 1
*
*
* ,
* .
* .
* .
* ,
*
* r
*
* n
*
*
* )
*
*
* {\displaystyle s(r_{1},...,r_{n})}
* as the solution of*
*
*
*
*
* 1
* n
*
*
*
* ∑
*
* i
* =
* 1
*
*
* n
*
*
* ρ
* (
*
* r
*
* i
*
*
*
* /
*
* s
* )
* =
* K
*
*
* {\textstyle {\frac {1}{n}}\sum _{i=1}^{n}\rho (r_{i}/s)=K}
* ,
* where
*
*
*
* K
*
*
* {\displaystyle K}
* is the expectation value of
*
*
*
* ρ
*
*
* {\displaystyle \rho }
* for a standard normal distribution. (If there are more solutions to the above equation, then we take the one with the smallest solution for s; if there is no solution, then we put
*
*
*
* s
* (
*
* r
*
* 1
*
*
* ,
* .
* .
* .
* ,
*
* r
*
* n
*
*
* )
* =
* 0
*
*
* {\displaystyle s(r_{1},...,r_{n})=0}
* .)
* Definition:
* Let
*
*
*
* (
*
* x
*
* 1
*
*
* ,
*
* y
*
* 1
*
*
* )
* ,
* .
* .
* .
* ,
* (
*
* x
*
* n
* ...
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