2e:null 2f:["$","title",null,{"children":"WebR glm() In Observable | boB Rudis | Observable"}] 34:T56b,```r meta <- readRDS(url("https://rud.is/data/tags.rds")) tags <- meta$metadata table( tags$created_at, dnn = "created_at" ) |> as.data.frame.table( responseName = "n", stringsAsFactors = FALSE ) |> transform( created_at = as.Date(created_at) ) -> xdf data.frame( created_at = seq.Date(min(xdf$created_at), max(xdf$created_at), "1 day") ) |> merge( xdf, all.x = TRUE ) |> transform( n = ifelse(is.na(n), 0, n), days_elapsed = as.numeric(created_at - min(created_at)) ) |> transform( csum = cumsum(n) ) -> xdf poisson_model <- glm(csum ~ days_elapsed, data = xdf, family = poisson(link = "log")) target_csum <- 2000 predicted_days_elapsed <-xdf$days_elapsed predictions <- vector("list", 2000) p_idx <- 0 while(TRUE) { predicted_days_elapsed <- max(predicted_days_elapsed) + 1 predicted_csum <- predict(poisson_model, newdata = data.frame(days_elapsed = predicted_days_elapsed), type = "response") p_idx <- p_idx + 1 data.frame( created_at = min(xdf$created_at) + predicted_days_elapsed, predicted_count = as.integer(predicted_csum) ) -> predictions[[p_idx]] if (predicted_csum >= target_csum) break } predicted_date <- min(xdf$created_at) + as.integer(predicted_days_elapsed) ydf <- do.call(rbind.data.frame, predictions) ydf$created_at <- as.character(ydf$created_at) ydf ```35:[] 32:{"id":"b8336b39e60d2ca0","slug":"webr-glm-in-observable","title":"WebR glm() In Observable","thumbnail":"36de30d81eb1ebb0530d94a8c40df3f11baab31cbd5f8532657c0878ce259321","access_level":"public","create_time":"$D2023-11-23T11:15:56.841Z","update_time":"$D2023-11-23T14:25:57.825Z","view_time":null,"first_public_time":"$D2023-11-23T11:48:30.912Z","has_unpublished_edits":null,"fork":false,"stars":1,"starred":false,"owner":{"type":"team","id":"0b35eed5f0115bfa","login":"hrbrmstr","name":"boB 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loading…`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":101,"value":"Plot.plot({\n x: {\n grid: true\n },\n y: {\n grid: true\n },\n marks: [\n Plot.lineY(predicted, { x: \"created_at\", y: \"predicted_count\", tip: true })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":89,"value":"predicted","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":83,"value":"predicted = webRDataFrameToJS(await rPredict.toJs()).map((d) => ({\n created_at: new Date(d.created_at),\n predicted_count: d.predicted_count\n}))","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":39,"value":"rPredict = await 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