query: R's lm(), get x when y is known
positive_passages.docid: 17989
positive_passages.text: Error bars, linear regression and "standard deviation" for point
negative_passages.docid: 114028
negative_passages.text: Obtaining predicted values (Y=1 or 0) from a logistic regression model fit
negative_passages.docid: 40017
negative_passages.text: Multiple Regression in R with y as a Factor
negative_passages.docid: 9356
negative_passages.text: Derivation of the formula for Ordinary Least Squares Linear Regression
negative_passages.docid: 122089
negative_passages.text: Singular information matrix error in lrm.fit in R
negative_passages.docid: 136919
negative_passages.text: Finding the likelihood function of parameter vector
negative_passages.docid: 20900
negative_passages.text: Regression without intercept: deriving $\hat{\beta}_1$ in least squares (no matrices)
negative_passages.docid: 92501
negative_passages.text: Fitting simple linear regression with no intercept
negative_passages.docid: 52681
negative_passages.text: Formula for an ARIMA(1,1,1) solving for y
negative_passages.docid: 79504
negative_passages.text: Analytical solution of a simple regression with fixed intercept
negative_passages.docid: 64856
negative_passages.text: Finding $E(X\mid X>Y)$ when $X,Y$ are i.i.d $U(0,1)$
negative_passages.docid: 142074
negative_passages.text: Solving linear regression with weights and constraints
negative_passages.docid: 130496
negative_passages.text: How do I fit a constrained regression in R so that coefficients total = 1?
negative_passages.docid: 143744
negative_passages.text: Calculate E[X] from incomplete data?
negative_passages.docid: 117183
negative_passages.text: Deriving the maximum likelihood for the parameters in linear regression
negative_passages.docid: 113333
negative_passages.text: How to estimate $P(x\le0)$ from $n$ samples of $x$?
negative_passages.docid: 105482
negative_passages.text: Interpreting summary function for lm model in R