This **crossword clue** is for the definition: *“Fine with me”.*

it’s A 26 letters **crossword puzzle definition**.

Next time, when searching for online help with your puzzle, try using the search term ““Fine with me” crossword” or ““Fine with me” crossword clue”. The possible answerss for “Fine with me” are listed below.

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## Possible Answers: **SURE**.

Last seen on: LA Times Crossword 15 Oct 18, Monday

### Random information on the term ““Fine with me””:

E (named e /iː/, plural ees)[1] is the fifth letter and the second vowel in the modern English alphabet and the ISO basic Latin alphabet. It is the most commonly used letter in many languages, including Czech, Danish, Dutch, English, French, German, Hungarian, Latin, Latvian, Norwegian, Spanish, and Swedish.[2][3][4][5][6]

The Latin letter ‘E’ differs little from its source, the Greek letter epsilon, ‘Ε’. This in turn comes from the Semitic letter hê, which has been suggested to have started as a praying or calling human figure (hillul ‘jubilation’), and was probably based on a similar Egyptian hieroglyph that indicated a different pronunciation. In Semitic, the letter represented /h/ (and /e/ in foreign words); in Greek, hê became the letter epsilon, used to represent /e/. The various forms of the Old Italic script and the Latin alphabet followed this usage.

Although Middle English spelling used ⟨e⟩ to represent long and short /e/, the Great Vowel Shift changed long /eː/ (as in ‘me’ or ‘bee’) to /iː/ while short /ɛ/ (as in ‘met’ or ‘bed’) remained a mid vowel. In other cases, the letter is silent, generally at the end of words.

### Random information on the term “SURE”:

In econometrics, the seemingly unrelated regressions (SUR)[1]:306[2]:279[3]:332 or seemingly unrelated regression equations (SURE)[4][5]:2 model, proposed by Arnold Zellner in (1962), is a generalization of a linear regression model that consists of several regression equations, each having its own dependent variable and potentially different sets of exogenous explanatory variables. Each equation is a valid linear regression on its own and can be estimated separately, which is why the system is called seemingly unrelated,[3]:332 although some authors suggest that the term seemingly related would be more appropriate,[1]:306 since the error terms are assumed to be correlated across the equations.

The model can be estimated equation-by-equation using standard ordinary least squares (OLS). Such estimates are consistent, however generally not as efficient as the SUR method, which amounts to feasible generalized least squares with a specific form of the variance-covariance matrix. Two important cases when SUR is in fact equivalent to OLS are when the error terms are in fact uncorrelated between the equations (so that they are truly unrelated) and when each equation contains exactly the same set of regressors on the right-hand-side.