I have the log-likelihood function: $ $ l(\overrightarrow\beta)=\sum_{i=1}^n [y_i log(p(\overrightarrow x_i;\overrightarrow\beta))+(1-y_i)log(1-p(\overrightarrow x_i;\overrightarrow\beta)] $ $ where $ p(\overrightarrow x_i;\overrightarrow\beta)=\frac{e^{{\overrightarrow\beta^T}\overrightarrow x_i}}{{1+\overrightarrow\beta^T}\overrightarrow x_i} $ where $ \overrightarrow\beta=(0,\beta_1)^T$ is the parameter vector and $ \overrightarrow x$ is the matrix of inputs, whose first column is all 1’s. The two classes are $ y_i=0$ or $ 1$ , and sinceRead more