# Difference between revisions of "Documentation:Monte Carlo Equilibration"

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− | We have a timeseries of N measurements obtained from a Monte Carlo simulation, i.e. <math>y_0,y_1,\cdots,y_{N-1}</math>. Suppose <math>\bar{y}_i = \beta_0 + \beta_1 x_i </math> (s.t. <math>i = 0, 1, \cdots, N-1</math>) is the least-squares best fitted line, we attempt to minimize | + | We have a timeseries of N measurements obtained from a Monte Carlo simulation, i.e. <math>y_0,y_1,\cdots,y_{N-1}</math>. |

+ | |||

+ | Suppose <math>\bar{y}_i = \beta_0 + \beta_1 x_i </math> (s.t. <math>i = 0, 1, \cdots, N-1</math>) is the least-squares best fitted line, we attempt to minimize |

## Revision as of 11:54, 9 September 2013

# Monte Carlo equilibration

## Theory

We have a timeseries of N measurements obtained from a Monte Carlo simulation, i.e. .

Suppose (s.t. ) is the least-squares best fitted line, we attempt to minimize