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Hat notation

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Mathematical notation
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(May 2024)

A "hat" (circumflex (ˆ)), placed over a symbol is a mathematical notation with various uses.

Estimated value

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In statistics, a circumflex (ˆ), called a "hat", is used to denote an estimator or an estimated value.[1] For example, in the context of errors and residuals, the "hat" over the letter ε ^ {\displaystyle {\hat {\varepsilon }}} {\displaystyle {\hat {\varepsilon }}} indicates an observable estimate (the residuals) of an unobservable quantity called ε {\displaystyle \varepsilon } {\displaystyle \varepsilon } (the statistical errors).

Another example of the hat operator denoting an estimator occurs in simple linear regression. Assuming a model of y i = β 0 + β 1 x i + ε i {\displaystyle y_{i}=\beta _{0}+\beta _{1}x_{i}+\varepsilon _{i}} {\displaystyle y_{i}=\beta _{0}+\beta _{1}x_{i}+\varepsilon _{i}}, with observations of independent variable data x i {\displaystyle x_{i}} {\displaystyle x_{i}} and dependent variable data y i {\displaystyle y_{i}} {\displaystyle y_{i}}, the estimated model is of the form y ^ i = β ^ 0 + β ^ 1 x i {\displaystyle {\hat {y}}_{i}={\hat {\beta }}_{0}+{\hat {\beta }}_{1}x_{i}} {\displaystyle {\hat {y}}_{i}={\hat {\beta }}_{0}+{\hat {\beta }}_{1}x_{i}} where i ( y i y ^ i ) 2 {\displaystyle \sum _{i}(y_{i}-{\hat {y}}_{i})^{2}} {\displaystyle \sum _{i}(y_{i}-{\hat {y}}_{i})^{2}} is commonly minimized via least squares by finding optimal values of β ^ 0 {\displaystyle {\hat {\beta }}_{0}} {\displaystyle {\hat {\beta }}_{0}} and β ^ 1 {\displaystyle {\hat {\beta }}_{1}} {\displaystyle {\hat {\beta }}_{1}} for the observed data.

Hat matrix

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Main article: hat matrix

In statistics, the hat matrix H projects the observed values y of response variable to the predicted values ŷ:

y ^ = H y . {\displaystyle {\hat {\mathbf {y} }}=H\mathbf {y} .} {\displaystyle {\hat {\mathbf {y} }}=H\mathbf {y} .}

Cross product

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In screw theory, one use of the hat operator is to represent the cross product operation. Since the cross product is a linear transformation, it can be represented as a matrix. The hat operator takes a vector and transforms it into its equivalent matrix.

a × b = a ^ b {\displaystyle \mathbf {a} \times \mathbf {b} =\mathbf {\hat {a}} \mathbf {b} } {\displaystyle \mathbf {a} \times \mathbf {b} =\mathbf {\hat {a}} \mathbf {b} }

For example, in three dimensions,

a × b = [ a x a y a z ] × [ b x b y b z ] = [ 0 a z a y a z 0 a x a y a x 0 ] [ b x b y b z ] = a ^ b {\displaystyle \mathbf {a} \times \mathbf {b} ={\begin{bmatrix}a_{x}\\a_{y}\\a_{z}\end{bmatrix}}\times {\begin{bmatrix}b_{x}\\b_{y}\\b_{z}\end{bmatrix}}={\begin{bmatrix}0&-a_{z}&a_{y}\\a_{z}&0&-a_{x}\\-a_{y}&a_{x}&0\end{bmatrix}}{\begin{bmatrix}b_{x}\\b_{y}\\b_{z}\end{bmatrix}}=\mathbf {\hat {a}} \mathbf {b} } {\displaystyle \mathbf {a} \times \mathbf {b} ={\begin{bmatrix}a_{x}\\a_{y}\\a_{z}\end{bmatrix}}\times {\begin{bmatrix}b_{x}\\b_{y}\\b_{z}\end{bmatrix}}={\begin{bmatrix}0&-a_{z}&a_{y}\\a_{z}&0&-a_{x}\\-a_{y}&a_{x}&0\end{bmatrix}}{\begin{bmatrix}b_{x}\\b_{y}\\b_{z}\end{bmatrix}}=\mathbf {\hat {a}} \mathbf {b} }

Unit vector

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Main article: Unit vector

In mathematics, a unit vector in a normed vector space is a vector (often a spatial vector) of length 1. A unit vector is often denoted by a lowercase letter with a circumflex, or "hat", as in v ^ {\displaystyle {\hat {\mathbf {v} }}} {\displaystyle {\hat {\mathbf {v} }}} (pronounced "v-hat").[2] [1] This is especially common in physics context.

Fourier transform

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The Fourier transform of a function f {\displaystyle f} {\displaystyle f} is traditionally denoted by f ^ {\displaystyle {\hat {f}}} {\displaystyle {\hat {f}}}.

Operator

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In quantum mechanics, operators are denoted with hat notation. For instance, see the time-independent Schrödinger equation, where the Hamiltonian operator is denoted H ^ {\displaystyle {\hat {H}}} {\displaystyle {\hat {H}}}.

H ^ ψ = E ψ {\displaystyle {\hat {H}}\psi =E\psi } {\displaystyle {\hat {H}}\psi =E\psi }

See also

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References

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  1. ^ a b Weisstein, Eric W. "Hat". mathworld.wolfram.com. Retrieved 2024年08月29日.
  2. ^ Barrante, James R. (2016年02月10日). Applied Mathematics for Physical Chemistry: Third Edition. Waveland Press. Page 124, Footnote 1. ISBN 978-1-4786-3300-6.


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